AI for Pulmonology: Chest Imaging and Respiratory Disease

Module: Healthcare AI | Difficulty: Advanced

Lung Volume Measurement

nodule Volume Doubling Time

Pulmonary AI Performance

import torch
import torch.nn as nn

class ChestXrayClassifier(nn.Module):
    def __init__(self, num_classes=14):
        super().__init__()
        self.backbone = models.densenet121(pretrained=True)
        num_features = self.backbone.classifier.in_features
        self.backbone.classifier = nn.Identity()
        self.classifier = nn.Sequential(
            nn.Linear(num_features, 512), nn.ReLU(),
            nn.Dropout(0.5), nn.Linear(512, num_classes))

    def forward(self, x):
        features = self.backbone(x)
        return self.classifier(features)

class COVIDClassifier(nn.Module):
    def __init__(self):
        super().__init__()
        self.features = nn.Sequential(
            nn.Conv2d(3, 64, 3, padding=1), nn.BatchNorm2d(64), nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(64, 128, 3, padding=1), nn.BatchNorm2d(128), nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(128, 256, 3, padding=1), nn.BatchNorm2d(256), nn.ReLU(),
            nn.AdaptiveAvgPool2d(1))
        self.classifier = nn.Linear(256, 3)

    def forward(self, x):
        features = self.features(x).flatten(1)
        return self.classifier(features)

def compute_covid_severity(ground_glass_vol, consolidation_vol, total_lung_vol):
    involvement = (ground_glass_vol + consolidation_vol) / total_lung_vol
    ggo_ratio = ground_glass_vol / (ground_glass_vol + consolidation_vol + 1e-6)
    severity_score = 100 * (0.7 * involvement + 0.3 * (1 - ggo_ratio))
    if severity_score < 25:
        severity = 'Mild'
    elif severity_score < 50:
        severity = 'Moderate'
    elif severity_score < 75:
        severity = 'Severe'
    else:
        severity = 'Critical'
    return severity_score, severity

model = ChestXrayClassifier(num_classes=14)
x = torch.randn(1, 3, 224, 224)
output = model(x)
print(f'Chest X-ray predictions: {output.shape}')

score, severity = compute_covid_severity(500, 200, 5000)
print(f'COVID severity: {score:.1f} ({severity})')

Research Insight: Chest X-ray AI has achieved expert-level performance for many conditions but faces challenges with rare pathologies. The COVID-19 pandemic highlighted both the potential and limitations of AI screening: rapid deployment was possible, but models trained on early pandemic data showed poor generalization to new variants and different populations.