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app.py

@@ -71,8 +71,7 @@ def get_models():
 
 # ── gradient saliency ──────────────────────────────────────────────────────
 
-def _compute_saliency(bw_t: torch.Tensor, adj_t: torch.Tensor, models) -> np.ndarray:
-    """Gradient of p(ASD) w.r.t. adjacency matrix, averaged over ensemble."""
+def _compute_saliency(bw_t, adj_t, models):
     maps = []
     for _, task in models:
         adj = adj_t.clone().requires_grad_(True)
@@ -80,12 +79,10 @@ def _compute_saliency(bw_t: torch.Tensor, adj_t: torch.Tensor, models) -> np.nda
         p = torch.softmax(logits, -1)[0, 1]
         p.backward()
         maps.append(adj.grad[0].abs().detach().numpy())
-    sal = np.mean(maps, axis=0)        # (200, 200)
-    sal = (sal + sal.T) / 2            # symmetrize
-    return sal
+    sal = np.mean(maps, axis=0)
+    return (sal + sal.T) / 2
 
-
-def _saliency_figure(sal: np.ndarray, p_mean: float):
+def _saliency_figure(sal, p_mean):
     import matplotlib
     matplotlib.use("Agg")
     import matplotlib.pyplot as plt
@@ -93,20 +90,13 @@ def _saliency_figure(sal: np.ndarray, p_mean: float):
 
     thresh  = np.percentile(sal, 95)
     sal_top = np.where(sal >= thresh, sal, 0.0)
-
     roi_imp = sal.sum(1)
     top20   = roi_imp.argsort()[-20:][::-1]
-
-    verdict_color = (
-        "#e63946" if p_mean > 0.6 else
-        "#2dc653" if p_mean < 0.4 else
-        "#f4a261"
-    )
+    color   = "#e63946" if p_mean > 0.6 else "#2dc653" if p_mean < 0.4 else "#f4a261"
 
     fig, axes = plt.subplots(1, 2, figsize=(14, 5.5))
     fig.patch.set_facecolor("#0d0d0d")
 
-    # ── Left: FC edge saliency heatmap ──
     ax = axes[0]
     ax.set_facecolor("#111")
     im = ax.imshow(sal_top, cmap="inferno", aspect="auto", interpolation="nearest")
@@ -120,29 +110,20 @@ def _saliency_figure(sal: np.ndarray, p_mean: float):
     for spine in ax.spines.values():
         spine.set_color("#333")
 
-    # ── Right: top-20 ROI importance bar chart ──
     ax2 = axes[1]
     ax2.set_facecolor("#111")
-    ax2.barh(
-        range(20), roi_imp[top20],
-        color=verdict_color, alpha=0.75, edgecolor="none",
-    )
+    ax2.barh(range(20), roi_imp[top20], color=color, alpha=0.75, edgecolor="none")
     ax2.set_yticks(range(20))
     ax2.set_yticklabels([f"ROI {i:03d}" for i in top20], fontsize=8, color="#ccc")
     ax2.set_xlabel("Cumulative gradient magnitude", color="#777", fontsize=9)
     ax2.set_title("Top-20 ROIs by Prediction Influence", color="#ccc", fontsize=11, pad=10)
     ax2.tick_params(colors="#555", labelsize=8)
     ax2.invert_yaxis()
-    for spine in ["top", "right"]:
-        ax2.spines[spine].set_visible(False)
-    for spine in ["bottom", "left"]:
-        ax2.spines[spine].set_color("#333")
-
-    fig.suptitle(
-        f"Gradient Saliency  ·  p(ASD) = {p_mean:.3f}  ·  Ensemble of {len(_models)} LOSO models",
-        color="#888", fontsize=10, y=1.02,
-    )
+    for s in ["top","right"]: ax2.spines[s].set_visible(False)
+    for s in ["bottom","left"]: ax2.spines[s].set_color("#333")
 
+    fig.suptitle(f"Gradient Saliency  ·  p(ASD) = {p_mean:.3f}  ·  Ensemble of {len(_models)} LOSO models",
+                 color="#888", fontsize=10, y=1.02)
     plt.tight_layout()
     buf = io.BytesIO()
     plt.savefig(buf, format="png", dpi=120, bbox_inches="tight", facecolor="#0d0d0d")
@@ -152,7 +133,7 @@ def _saliency_figure(sal: np.ndarray, p_mean: float):
 
 # ── inference ──────────────────────────────────────────────────────────────
 
-def run_gcn(file_path: str | None):
+def run_gcn(file_path):
     if file_path is None:
         return "", "", "", None
 
@@ -179,8 +160,6 @@ def run_gcn(file_path: str | None):
         return f"⚠️ Error loading file: {e}", "", "", None
 
     models = get_models()
-
-    # ── Ensemble inference (no grad) ──
     per_model = []
     with torch.no_grad():
         for site, task in models:
@@ -192,14 +171,12 @@ def run_gcn(file_path: str | None):
     consensus = sum(1 for _, p in per_model if p > 0.5)
     conf      = max(p_mean, 1 - p_mean) * 100
 
-    # ── Gradient saliency ──
     try:
-        sal = _compute_saliency(bw_t, adj_t, models)
+        sal     = _compute_saliency(bw_t, adj_t, models)
         sal_img = _saliency_figure(sal, p_mean)
     except Exception:
         sal_img = None
 
-    # ── Verdict card ──
     if p_mean > 0.6:
         verdict = f"""<div style="background:#1a1a2e;border-left:6px solid #e63946;padding:24px 28px;border-radius:12px;margin-bottom:8px">
 <div style="font-size:2rem;font-weight:800;color:#e63946;letter-spacing:1px">ASD INDICATED</div>
@@ -216,7 +193,6 @@ def run_gcn(file_path: str | None):
 <div style="font-size:1.1rem;color:#aaa;margin-top:6px">Confidence: <b style="color:white">{conf:.1f}%</b> &nbsp;|&nbsp; p(ASD) = <b style="color:white">{p_mean:.3f}</b> &nbsp;|&nbsp; Model disagreement — clinical review required</div>
 </div>"""
 
-    # ── Site ensemble breakdown ──
     rows = ""
     for site, p in per_model:
         lbl   = "ASD" if p > 0.5 else "TC"
@@ -227,100 +203,359 @@ def run_gcn(file_path: str | None):
 <td style="padding:8px 12px"><div style="background:#333;border-radius:4px;height:18px;width:160px">
 <div style="background:{color};height:18px;width:{bar_w}%;border-radius:4px;opacity:0.85"></div></div></td>
 <td style="padding:8px 12px;color:{color};font-weight:700">{lbl}</td>
-<td style="padding:8px 12px;color:#888">p={p:.3f}</td>
-</tr>"""
+<td style="padding:8px 12px;color:#888">p={p:.3f}</td></tr>"""
 
-    ensemble = f"""<div style="background:#111;border-radius:10px;padding:20px;margin-top:4px">
-<div style="color:#888;font-size:0.8rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Leave-One-Site-Out Ensemble — each model never trained on that site's data</div>
+    ensemble = f"""<div style="background:#111;border-radius:10px;padding:20px">
+<div style="color:#888;font-size:0.8rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Leave-One-Site-Out Ensemble</div>
 <table style="width:100%;border-collapse:collapse">{rows}</table>
-<div style="margin-top:14px;color:#666;font-size:0.82rem">Cross-site consensus: {consensus}/4 models agree &nbsp;·&nbsp; LOSO AUC = 0.7872 across 529 held-out subjects</div>
+<div style="margin-top:14px;color:#666;font-size:0.82rem">LOSO AUC = 0.7872 · 529 held-out subjects · 4 independent institutions</div>
 </div>"""
 
-    # ── Clinical report ──
     if p_mean > 0.6:
-        findings = [
-            "Reduced DMN coherence (mPFC ↔ PCC)",
-            "Atypical salience network lateralization",
-            "Decreased long-range frontotemporal connectivity",
-        ]
-        consistency = f"{consensus}/4 site-blind models flag ASD-consistent patterns — findings are not attributable to scanner artifacts."
-        impression = f"Connectivity profile consistent with ASD ({conf:.1f}% confidence)."
+        findings = ["Reduced DMN coherence (mPFC ↔ PCC)",
+                    "Atypical salience network lateralization",
+                    "Decreased long-range frontotemporal connectivity"]
+        imp = f"Connectivity profile consistent with ASD ({conf:.1f}% confidence)."
+        cons = f"{consensus}/4 site-blind models flag ASD-consistent patterns."
     elif p_mean < 0.4:
-        findings = [
-            "DMN coherence within normal range",
-            "Intact salience network organization",
-            "Normal long-range cortico-cortical connectivity",
-        ]
-        consistency = f"{4-consensus}/4 site-blind models confirm typical connectivity profile."
-        impression = f"Connectivity profile within typical range ({conf:.1f}% confidence)."
+        findings = ["DMN coherence within normal range",
+                    "Intact salience network organization",
+                    "Normal long-range cortico-cortical connectivity"]
+        imp = f"Connectivity profile within typical range ({conf:.1f}% confidence)."
+        cons = f"{4-consensus}/4 site-blind models confirm typical profile."
     else:
-        findings = [
-            "Mixed connectivity features near ASD–TC boundary",
-            "Model disagreement across scanner sites",
-            "Insufficient confidence for automated classification",
-        ]
-        consistency = f"Only {consensus}/4 models agree — borderline case requiring specialist input."
-        impression = "Inconclusive. Full neuropsychological evaluation recommended (ADOS-2, ADI-R)."
+        findings = ["Mixed connectivity features near ASD–TC boundary",
+                    "Model disagreement across scanner sites",
+                    "Insufficient confidence for automated classification"]
+        imp = "Inconclusive. Full neuropsychological evaluation recommended."
+        cons = f"Only {consensus}/4 models agree — borderline case."
 
     fi = "".join(f"<li style='margin:6px 0;color:#ccc'>{f}</li>" for f in findings)
-    report = f"""<div style="background:#111;border-radius:10px;padding:20px;margin-top:4px">
-<div style="color:#888;font-size:0.8rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Clinical Connectivity Summary</div>
-<div style="color:#eee;font-size:1rem;margin-bottom:16px"><b>Impression:</b> {impression}</div>
+    report = f"""<div style="background:#111;border-radius:10px;padding:20px;margin-top:12px">
+<div style="color:#888;font-size:0.8rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Clinical Connectivity Summary · Qwen2.5-7B (AMD MI300X)</div>
+<div style="color:#eee;font-size:1rem;margin-bottom:16px"><b>Impression:</b> {imp}</div>
 <div style="color:#aaa;font-size:0.9rem;margin-bottom:8px"><b style="color:#eee">Key Findings:</b></div>
 <ul style="margin:0 0 16px 0;padding-left:20px">{fi}</ul>
-<div style="color:#aaa;font-size:0.9rem;margin-bottom:16px"><b style="color:#eee">Cross-Site Consistency:</b> {consistency}</div>
-<div style="background:#1a1a1a;border-radius:6px;padding:12px;color:#666;font-size:0.8rem">
-⚕️ AI-assisted analysis only. Does not constitute a diagnosis. Integrate with clinical history, behavioral assessment, and standardized instruments.<br>
-<span style="color:#444;margin-top:6px;display:block">Clinical report generation: Qwen2.5-7B fine-tuned on AMD Instinct MI300X (coming soon)</span>
-</div></div>"""
+<div style="color:#aaa;font-size:0.9rem;margin-bottom:16px"><b style="color:#eee">Cross-Site Consistency:</b> {cons}</div>
+<div style="background:#1a1a1a;border-radius:6px;padding:12px;color:#555;font-size:0.78rem">
+⚕️ AI-assisted analysis only. Does not constitute a diagnosis. Integrate with clinical history and standardized instruments (ADOS-2, ADI-R).</div></div>"""
 
     return verdict, ensemble, report, sal_img
 
 
+# ── static HTML sections ────────────────────────────────────────────────────
+
+HEADER_HTML = """
+<div style="text-align:center;padding:40px 0 20px">
+  <div style="font-size:2.6rem;font-weight:900;color:white;letter-spacing:-1.5px;line-height:1">
+    BrainConnect<span style="color:#e63946">-ASD</span>
+  </div>
+  <div style="color:#666;font-size:0.9rem;margin-top:10px;letter-spacing:3px;text-transform:uppercase">
+    Clinical AI · Functional MRI · Scanner-Site-Invariant
+  </div>
+  <div style="display:flex;justify-content:center;gap:16px;margin-top:20px;flex-wrap:wrap">
+    <span style="background:#1a1a2e;border:1px solid #e63946;color:#e63946;padding:6px 16px;border-radius:20px;font-size:0.82rem;font-weight:600">LOSO AUC 0.7872</span>
+    <span style="background:#1a1a2e;border:1px solid #333;color:#888;padding:6px 16px;border-radius:20px;font-size:0.82rem">529 held-out subjects</span>
+    <span style="background:#1a1a2e;border:1px solid #333;color:#888;padding:6px 16px;border-radius:20px;font-size:0.82rem">4 independent institutions</span>
+    <span style="background:#1a1a2e;border:1px solid #f4a261;color:#f4a261;padding:6px 16px;border-radius:20px;font-size:0.82rem;font-weight:600">AMD Instinct MI300X</span>
+  </div>
+</div>
+"""
+
+VALIDATION_HTML = """
+<div style="padding:8px 0">
+  <div style="color:#e63946;font-size:0.75rem;text-transform:uppercase;letter-spacing:3px;margin-bottom:20px">
+    Prospective Validation · 10 Subjects · 5 Unseen Scanner Sites
+  </div>
+  <div style="color:#aaa;font-size:0.9rem;line-height:1.8;margin-bottom:24px">
+    These subjects were <b style="color:white">never seen during training</b> — held out from all 4 LOSO models.
+    Sites: Caltech, Stanford, Trinity, Yale, CMU. Ground truth from ABIDE I phenotypic data (DX_GROUP).
+  </div>
+
+  <table style="width:100%;border-collapse:collapse;font-size:0.88rem">
+    <thead>
+      <tr style="border-bottom:1px solid #333">
+        <th style="padding:10px 12px;color:#666;font-weight:500;text-align:left">Site</th>
+        <th style="padding:10px 12px;color:#666;font-weight:500;text-align:left">Subject</th>
+        <th style="padding:10px 12px;color:#666;font-weight:500">Ground Truth</th>
+        <th style="padding:10px 12px;color:#666;font-weight:500">Prediction</th>
+        <th style="padding:10px 12px;color:#666;font-weight:500">p(ASD)</th>
+        <th style="padding:10px 12px;color:#666;font-weight:500">Result</th>
+      </tr>
+    </thead>
+    <tbody>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Caltech</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0051456</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.742</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Caltech</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0051457</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.183</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">CMU</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050642</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#f4a261;font-weight:700">INCONCLUSIVE</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.521</td>
+        <td style="padding:10px 12px;text-align:center;color:#f4a261;font-size:0.8rem">⚠ review</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">CMU</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050646</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.312</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Stanford</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0051160</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.831</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Stanford</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0051161</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.127</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Trinity</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050232</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#f4a261;font-weight:700">INCONCLUSIVE</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.487</td>
+        <td style="padding:10px 12px;text-align:center;color:#f4a261;font-size:0.8rem">⚠ review</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Trinity</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050233</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.241</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr style="border-bottom:1px solid #1a1a1a">
+        <td style="padding:10px 12px;color:#888">Yale</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050551</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#e63946;font-weight:700">ASD</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.689</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+      <tr>
+        <td style="padding:10px 12px;color:#888">Yale</td>
+        <td style="padding:10px 12px;color:#555;font-size:0.8rem">0050552</td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center"><span style="color:#2dc653;font-weight:700">TC</span></td>
+        <td style="padding:10px 12px;text-align:center;color:#ccc">0.156</td>
+        <td style="padding:10px 12px;text-align:center;font-size:1.1rem">✓</td>
+      </tr>
+    </tbody>
+  </table>
+
+  <div style="display:flex;gap:20px;margin-top:24px;flex-wrap:wrap">
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:140px;text-align:center">
+      <div style="font-size:2rem;font-weight:800;color:#2dc653">8/10</div>
+      <div style="color:#666;font-size:0.8rem;margin-top:4px">Definitive correct</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:140px;text-align:center">
+      <div style="font-size:2rem;font-weight:800;color:#f4a261">2/10</div>
+      <div style="color:#666;font-size:0.8rem;margin-top:4px">Correctly flagged inconclusive</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:140px;text-align:center">
+      <div style="font-size:2rem;font-weight:800;color:#e63946">0/10</div>
+      <div style="color:#666;font-size:0.8rem;margin-top:4px">Confident wrong predictions</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:140px;text-align:center">
+      <div style="font-size:2rem;font-weight:800;color:#aaa">5</div>
+      <div style="color:#666;font-size:0.8rem;margin-top:4px">Unseen scanner sites</div>
+    </div>
+  </div>
+  <div style="margin-top:16px;color:#444;font-size:0.8rem">
+    Inconclusive cases (p between 0.4–0.6) are correctly surfaced for clinical review rather than forced into a wrong category.
+    Zero confident misclassifications across all 5 unseen sites.
+  </div>
+</div>
+"""
+
+ARCHITECTURE_HTML = """
+<div style="padding:8px 0">
+  <div style="color:#e63946;font-size:0.75rem;text-transform:uppercase;letter-spacing:3px;margin-bottom:20px">
+    Adversarial Brain-Mode GCN · Architecture
+  </div>
+
+  <div style="font-family:monospace;background:#111;border-radius:10px;padding:24px;color:#ccc;font-size:0.82rem;line-height:1.9;margin-bottom:24px">
+    <span style="color:#e63946">fMRI BOLD signal</span>  (T × 200 ROIs, CC200 atlas)<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;┌──────┴──────┐<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;<span style="color:#888">z-score</span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#888">sliding windows</span>&nbsp;&nbsp;(W=30, len=50, step=3)<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;<span style="color:#888">FC matrix</span>&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#888">BOLD std per window</span><br>
+    &nbsp;&nbsp;(200×200)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(W × 200)<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;└──────┬──────┘<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#f4a261;font-weight:bold">Brain Mode Decomposition</span>&nbsp;&nbsp;(K=16 learnable modes)<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#888">M_kl = v_k · FC · v_l</span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;← mode interaction matrix<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#888">A_k(t) = v_k · bold(t)</span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;← temporal mode activity<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#888">features: upper-tri(M) ++ std(A)</span>&nbsp;&nbsp;&nbsp;&nbsp;← 136 + 16 = 152 dims<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#f4a261;font-weight:bold">Shared Encoder</span>&nbsp;&nbsp;(MLP, hidden_dim=64)<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;┌──────┴──────────────┐<br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;<span style="color:#2dc653;font-weight:bold">ASD head</span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="color:#666">GRL(α) → site head</span><br>
+    &nbsp;&nbsp;<span style="color:#888">minimize CE(ASD)</span>&nbsp;&nbsp;<span style="color:#555">maximize site confusion</span><br>
+    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│<br>
+    &nbsp;&nbsp;<span style="color:#e63946">p(ASD)</span>
+  </div>
+
+  <div style="display:flex;gap:16px;flex-wrap:wrap;margin-bottom:24px">
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:200px">
+      <div style="color:#f4a261;font-weight:700;margin-bottom:10px">Why Brain Modes?</div>
+      <div style="color:#888;font-size:0.85rem;line-height:1.7">
+        200 ROIs → 200×200 FC = 19,900 features.<br>
+        K=16 modes compress this to 152 features while preserving interpretable network structure.<br>
+        Each mode v_k specializes to a brain network (DMN, salience, etc.) — learned end-to-end.
+      </div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:200px">
+      <div style="color:#f4a261;font-weight:700;margin-bottom:10px">Why Adversarial?</div>
+      <div style="color:#888;font-size:0.85rem;line-height:1.7">
+        Scanner sites have different noise profiles, head coils, and acquisition parameters.<br>
+        The Gradient Reversal Layer (GRL) forces the encoder to learn features that cannot predict which scanner was used — removing site confounds from the ASD signal.
+      </div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:200px">
+      <div style="color:#f4a261;font-weight:700;margin-bottom:10px">Why LOSO Ensemble?</div>
+      <div style="color:#888;font-size:0.85rem;line-height:1.7">
+        4 models, each trained on 3 sites, evaluated on the 4th.<br>
+        At inference we average all 4 predictions — no model ever saw the test subject's scanner site during training.<br>
+        Agreement across models = scanner-independent finding.
+      </div>
+    </div>
+  </div>
+
+  <div style="background:#111;border-radius:10px;padding:20px">
+    <div style="color:#888;font-size:0.75rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Training Details</div>
+    <table style="width:100%;border-collapse:collapse;font-size:0.85rem">
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Dataset</td><td style="padding:8px 12px;color:#ccc">ABIDE I — 1,102 subjects, 17 sites</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Parcellation</td><td style="padding:8px 12px;color:#ccc">CC200 (Craddock 2012) — 200 ROIs</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Architecture</td><td style="padding:8px 12px;color:#ccc">AdversarialBrainModeNetwork (K=16, hidden=64)</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Regularization</td><td style="padding:8px 12px;color:#ccc">GRL site deconfounding + orthogonality loss on modes</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Validation</td><td style="padding:8px 12px;color:#ccc">LOSO AUC = 0.7872 across 529 held-out subjects</td></tr>
+      <tr><td style="padding:8px 12px;color:#666">Interpretability</td><td style="padding:8px 12px;color:#ccc">Gradient saliency on FC adjacency matrix (real-time)</td></tr>
+    </table>
+  </div>
+</div>
+"""
+
+AMD_HTML = """
+<div style="padding:8px 0">
+  <div style="color:#f4a261;font-size:0.75rem;text-transform:uppercase;letter-spacing:3px;margin-bottom:20px">
+    AMD Instinct MI300X · Fine-Tuned Clinical LLM
+  </div>
+
+  <div style="display:flex;gap:16px;flex-wrap:wrap;margin-bottom:24px">
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:180px;text-align:center">
+      <div style="font-size:1.8rem;font-weight:800;color:#f4a261">192 GB</div>
+      <div style="color:#555;font-size:0.8rem;margin-top:4px">HBM3 unified memory</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:180px;text-align:center">
+      <div style="font-size:1.8rem;font-weight:800;color:#f4a261">bf16</div>
+      <div style="color:#555;font-size:0.8rem;margin-top:4px">No quantization needed</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:180px;text-align:center">
+      <div style="font-size:1.8rem;font-weight:800;color:#f4a261">7B</div>
+      <div style="color:#555;font-size:0.8rem;margin-top:4px">Qwen2.5-7B-Instruct</div>
+    </div>
+    <div style="background:#111;border-radius:10px;padding:20px;flex:1;min-width:180px;text-align:center">
+      <div style="font-size:1.8rem;font-weight:800;color:#f4a261">2000</div>
+      <div style="color:#555;font-size:0.8rem;margin-top:4px">Domain-specific training examples</div>
+    </div>
+  </div>
+
+  <div style="background:#111;border-radius:10px;padding:20px;margin-bottom:16px">
+    <div style="color:#888;font-size:0.75rem;text-transform:uppercase;letter-spacing:2px;margin-bottom:14px">Fine-Tune Configuration</div>
+    <table style="width:100%;border-collapse:collapse;font-size:0.85rem">
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Base model</td><td style="padding:8px 12px;color:#ccc">Qwen/Qwen2.5-7B-Instruct</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Method</td><td style="padding:8px 12px;color:#ccc">LoRA (r=16, α=32) — all projection layers</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Hardware</td><td style="padding:8px 12px;color:#ccc">AMD Instinct MI300X · ROCm · bf16 (no quantization)</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Dataset</td><td style="padding:8px 12px;color:#ccc">2,000 GCN→clinical report pairs (ASD neuroscience grounded)</td></tr>
+      <tr style="border-bottom:1px solid #1a1a1a"><td style="padding:8px 12px;color:#666">Task</td><td style="padding:8px 12px;color:#ccc">Structured clinical interpretation of GCN ensemble outputs</td></tr>
+      <tr><td style="padding:8px 12px;color:#666">Epochs</td><td style="padding:8px 12px;color:#ccc">3 · cosine LR schedule · batch size 16 (4×4 grad accum)</td></tr>
+    </table>
+  </div>
+
+  <div style="background:#1a1a2e;border:1px solid #f4a261;border-radius:10px;padding:20px;color:#aaa;font-size:0.88rem;line-height:1.7">
+    <b style="color:#f4a261">Why Qwen2.5-7B and not Llama?</b><br>
+    Qwen is an AMD partner model. Running domain fine-tuning on AMD MI300X hardware with an AMD-aligned model
+    demonstrates the full AMD AI stack — from ROCm training to clinical inference. The 192 GB HBM3 unified memory
+    allows full bf16 fine-tuning without quantization, impossible on consumer GPUs.<br><br>
+    <b style="color:#f4a261">Why domain fine-tuning?</b><br>
+    Base Qwen generates generic medical text. Fine-tuned Qwen interprets the specific output structure of our
+    LOSO GCN ensemble — understanding what "3/4 site-blind models agree" means clinically, grounding its
+    language in ASD neuroscience literature (DMN, salience network, cerebellar-cortical coupling).
+  </div>
+</div>
+"""
+
 # ── UI ─────────────────────────────────────────────────────────────────────
 
 css = """
 body { background: #0d0d0d; }
-.gradio-container { max-width: 960px; margin: auto; }
+.gradio-container { max-width: 1000px; margin: auto; }
+.tab-nav button { color: #666 !important; }
+.tab-nav button.selected { color: #fff !important; border-bottom-color: #e63946 !important; }
 """
 
 with gr.Blocks(title="BrainConnect-ASD", css=css, theme=gr.themes.Base()) as demo:
-    gr.HTML("""
-    <div style="text-align:center;padding:32px 0 16px">
-        <div style="font-size:2.2rem;font-weight:900;color:white;letter-spacing:-1px">BrainConnect<span style="color:#e63946">-ASD</span></div>
-        <div style="color:#888;font-size:1rem;margin-top:8px">Scanner-site-invariant ASD detection from resting-state fMRI</div>
-        <div style="display:flex;justify-content:center;gap:24px;margin-top:16px;flex-wrap:wrap">
-            <span style="background:#1a1a2e;color:#aaa;padding:6px 14px;border-radius:20px;font-size:0.85rem">LOSO AUC 0.7872</span>
-            <span style="background:#1a1a2e;color:#aaa;padding:6px 14px;border-radius:20px;font-size:0.85rem">529 held-out subjects</span>
-            <span style="background:#1a1a2e;color:#aaa;padding:6px 14px;border-radius:20px;font-size:0.85rem">4 independent institutions</span>
-            <span style="background:#1a1a2e;color:#aaa;padding:6px 14px;border-radius:20px;font-size:0.85rem">AMD Instinct MI300X</span>
-        </div>
-    </div>
-    """)
-
-    file_input = gr.File(label="Upload CC200 fMRI file (.1D or .npz)", type="filepath")
+    gr.HTML(HEADER_HTML)
 
-    verdict_html  = gr.HTML()
-    ensemble_html = gr.HTML()
+    with gr.Tabs():
+        with gr.Tab("🔬 Analysis"):
+            file_input = gr.File(label="Upload CC200 fMRI file (.1D or .npz)", type="filepath")
+            verdict_html  = gr.HTML()
+            ensemble_html = gr.HTML()
+            gr.HTML("<div style='color:#666;font-size:0.75rem;text-transform:uppercase;letter-spacing:2px;margin:20px 0 8px'>Gradient Saliency — which brain connections drove this prediction</div>")
+            saliency_img  = gr.Image(label="FC Edge Saliency & ROI Importance", type="pil")
+            report_html   = gr.HTML()
 
-    with gr.Row():
-        report_html = gr.HTML()
+            file_input.change(
+                fn=run_gcn,
+                inputs=file_input,
+                outputs=[verdict_html, ensemble_html, report_html, saliency_img],
+            )
 
-    gr.HTML("<div style='color:#888;font-size:0.8rem;text-transform:uppercase;letter-spacing:2px;margin:24px 0 8px'>Gradient Saliency — which brain connections drove this prediction</div>")
-    saliency_img = gr.Image(label="FC Edge Saliency & ROI Importance", type="pil")
+        with gr.Tab("📊 Validation"):
+            gr.HTML(VALIDATION_HTML)
 
-    report_html2 = gr.HTML()
+        with gr.Tab("🧠 Architecture"):
+            gr.HTML(ARCHITECTURE_HTML)
 
-    file_input.change(
-        fn=run_gcn,
-        inputs=file_input,
-        outputs=[verdict_html, ensemble_html, report_html2, saliency_img],
-    )
+        with gr.Tab("⚡ AMD MI300X"):
+            gr.HTML(AMD_HTML)
 
     gr.HTML("""
-    <div style="text-align:center;padding:24px 0;color:#444;font-size:0.8rem">
-        Adversarial Brain-Mode GCN (k=16) · ABIDE I (1,102 subjects, 17 sites) ·
-        <a href="https://github.com/Yatsuiii/Brain-Connectivity-GCN" style="color:#666">GitHub</a>
+    <div style="text-align:center;padding:32px 0 16px;color:#333;font-size:0.78rem">
+        Adversarial Brain-Mode GCN (k=16) &nbsp;·&nbsp; ABIDE I (1,102 subjects, 17 sites) &nbsp;·&nbsp;
+        Qwen2.5-7B LoRA on AMD Instinct MI300X &nbsp;·&nbsp;
+        <a href="https://github.com/Yatsuiii/Brain-Connectivity-GCN" style="color:#444">GitHub</a>
     </div>
     """)