Artificial Intelligence
AI in Healthcare; AI in Finance; AI in Autonomous Vehicles
C-CAT
AI in Healthcare
| Application | Description | Technology |
|---|---|---|
| Medical Imaging | Detect tumors, fractures from X-ray/MRI/CT | CNN, U-Net |
| Drug Discovery | Find new drug molecules | AlphaFold, generative AI |
| Disease Diagnosis | Identify diseases from symptoms | Expert systems, DNN |
| Precision Medicine | Personalize treatment by genomics | Genomics + ML |
| Patient Monitoring | Track vitals continuously via wearables | IoT + Edge AI |
| Robot-Assisted Surgery | Precise minimally invasive surgery | Da Vinci system |
| Drug Interaction | Predict adverse drug interactions | Knowledge graphs |
| Mental Health | Chatbot therapy, mood monitoring | NLP, sentiment analysis |
AlphaFold — Groundbreaking Achievement
AlphaFold (DeepMind) is an AI system that predicts the 3D structure of proteins from their amino acid sequence.
- Solved a 50-year-old biology problem
- Predicted structure of 200 million proteins (nearly all known proteins)
- Freely released to the scientific community
- Could accelerate drug discovery by decades
AI in Finance
| Application | Description | Technology |
|---|---|---|
| Fraud Detection | Identify fraudulent transactions in real time | Anomaly detection, ML |
| Credit Scoring | Assess loan risk based on multiple factors | Gradient boosting (XGBoost) |
| Algorithmic Trading | Automated stock/forex trading | RL, time-series ML |
| Risk Assessment | Calculate portfolio and market risk | Simulation + ML |
| KYC Automation | Verify customer identity | NLP + OCR + CV |
| Chatbots | Customer financial advice | NLP |
| AML | Anti-money laundering pattern detection | Graph ML, anomaly detection |
| Insurance | Claims processing, fraud detection | NLP + CV |
AI in Autonomous Vehicles
SAE Levels of Autonomy
| Level | Name | Description | Example |
|---|---|---|---|
| Level 0 | No Automation | Human does everything | Traditional car |
| Level 1 | Driver Assistance | One feature (cruise control) | Adaptive cruise control |
| Level 2 | Partial Automation | Multiple features simultaneously | Tesla Autopilot |
| Level 3 | Conditional Automation | System drives; human ready to take over | Audi Traffic Jam Pilot |
| Level 4 | High Automation | No human needed in limited areas | Waymo Robotaxi |
| Level 5 | Full Automation | No human needed anywhere | Future autonomous vehicles |
Technologies in Autonomous Vehicles
| Technology | Role in AV |
|---|---|
| Camera | Lane detection, traffic sign recognition, pedestrian detection |
| LIDAR | 3D mapping of surroundings; measures distances precisely |
| RADAR | Detect objects and speed in bad weather (rain, fog) |
| GPS + HD Maps | Precise positioning (cm accuracy) |
| CNN | Object detection and classification from camera images |
| Sensor Fusion | Combine inputs from all sensors for robust perception |
| Path Planning | Calculate optimal, safe route in real time |
| Control System | Execute steering, braking, acceleration commands |
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