Machine Learning in Healthcare: 5 important developments you can’t afford to miss
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This document discusses 5 important developments in machine learning for healthcare: 1) Electronic health records can be accessed by stakeholders to understand past treatments. 2) Machine learning processes patient data to help identify diseases that are difficult to detect. 3) Algorithms allow drug manufacturers to design effective medical compositions. 4) Machine learning assists clinical trials by predicting suitable candidates. 5) It enables personalized healthcare by answering patient queries and monitoring health through apps and devices.
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Machine Learning in Healthcare: 5 important developments you can’t afford to miss
- 2. ELECTRONIC HEALTH RECORDS (EHR) EHRS can be accessed by different stakeholders who want to understand which treatments have worked in the past.
- 3. MEDICAL IMAGING & DIAGNOSIS Machine Learning processes patient data and helps in identifying diseases that might exist in the body but are hard to identify.
- 4. DRUG DISCOVERY & DEVELOPMENT Machine Learning algorithms allow pharma manufacturers to combine medical compositions and make decisions on what works the best.
- 5. CLINICAL TRIALS & RESEARCH Machine Learning assists researchers by predicting the most suitable candidates for clinical trials to minimize their chances of error.
- 6. PERSONALIZED HEALTHCARE Machine Learning for health care enables personal health by providing answers to common queries of patients through apps and monitor health through smart devics.
- 7. TALK TO OUR MACHINE LEARNING EXPERTS www.botreetechnologies.com