Interesting article related to 7 promising applications in healthcare on techemergence.com – https://www.techemergence.com/machine-learning-in-pharma-medicine/

1. Disease Identification/Diagnosis
Examples:
Cancer identification and treatment
Dosage trials for intravenous tumor treatment and detection and management of prostate cancer (Biopharma company Berg)
Address macular degeneration in aging eyes (Google’s DeepMind Health)
Diagnose and provide treatment for brain-based diseases like depression (Oxford’s P1vital® Predicting Response to Depression Treatment (PReDicT))

2. Personalized Treatment/Behavioral Modification
Examples:
Use patient medical information and history to optimize the selection of treatment options (IBM Watson Oncology)
Smoking cessation (Somatix)
Skin cancer risk app (SkinVision)

3. Drug Discovery and Manufacturing
Examples:
Understand disease processes and design for effective treatment of diseases like Type 2 diabetes (MIT Clinical Machine Learning Group)
Develop AI technology for cancer precision treatment (Microsoft’s Project Hanover)

4. Clinical Trial Research
Examples:
Identify candidates for clinical trials
Find best sample sizes
Address and adapt to differences in sites for patient recruitment
Use electronic medical records to reduce data errors
Remote monitoring and real-time data access for increased safety

5. Radiology and Radiotherapy
Examples:
Detect differences in healthy and cancerous tissues to help improve radiation treatments (Google’s DeepMind Health & University College London Hospital (UCLH))

6. Smart Electronic Health Records
Examples:
Document classification
Optical character recognition (MATLAB’s ML handwriting recognition, Google’s Cloud Vision API)
Intelligent electronic health records (MIT Clinical Machine Learning Group)

7. Epidemic Outbreak Prediction
Examples:
Malaria Outbreak Prediction
Predict outbreak severity in third-world countries (ProMED-mail)
Use automated classification and visualization to help monitor and provides alerts for disease outbreaks in any country (HealthMap)