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Updated by Julian Knight on Oct 23, 2017
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AI in Medicine

This online short course brought to you by MIT features weekly modules and flexible learning over a 6-week period with approximately 6-8 hours of work per week. You'll walk away from this course with:

1). A practical grounding in artificial intelligence (AI) and its business applications, equipping you with the knowledge and confidence you need to help you transform your organization into an innovative, efficient, and sustainable company of the future,

2) The ability to lead informed, strategic decision making and augment business performance by integrating key AI management and leadership insights into the way your organization operates, and

3) Recognition of your understanding of AI in the form of a certificate of completion from the MIT Sloan School of Management - one of the world’s leading business schools.

AlI Doctors will Become 'as Ubiquitous as Stethoscopes' | Health | WIRED

One of the biggest problems facing doctors isn't patients' injuries or illnesses – it's the sheer quantity data. Most will spend more time going over medical records than actually dealing with their patients.

It's a problem that "AI doctors" could help address, with supercomputers processing information far faster and more efficiently. The problem, IBM's Kyu Rhee tells the crowd at WIRED Health, is trust.

Physicians in everyday clinical practice are under pressure to innovate faster than ever because of the rapid, exponential growth in healthcare data. "Big data" refers to extremely large data sets that cannot be analyzed or interpreted using traditional data processing methods. In fact, big data itself is meaningless, but processing it offers the promise of unlocking novel insights and accelerating breakthroughs in medicine-which in turn has the potential to transform current clinical practice. Physicians can analyze big data, but at present it requires a large amount of time and sophisticated analytic tools such as supercomputers. However, the rise of artificial intelligence (AI) in the era of big data could assist physicians in shortening processing times and improving the quality of patient care in clinical practice. This editorial provides a glimpse at the potential uses of AI technology in clinical practice and considers the possibility of AI replacing physicians, perhaps altogether. Physicians diagnose diseases based on personal medical histories, individual biomarkers, simple scores (e.g., CURB-65, MELD), and their physical examinations of individual patients. In contrast, AI can diagnose diseases based on a complex algorithm using hundreds of biomarkers, imaging results from millions of patients, aggregated published clinical research from PubMed, and thousands of physician's notes from electronic health records (EHRs). While AI could assist physicians in many ways, it is unlikely to replace physicians in the foreseeable future. Let us look at the emerging uses of AI in medicine.

If medical data could talk, what would it say? is a conversational platform for on-demand, quantified biology. We are entering a world where artificial intelligence and natural language understanding are bringing unmatched benefits to healthcare. Our advanced natural language dialog system is designed for vertical medical domains, and can generate insights on blood, genomics, microbiome, environmental and anatomical data.

Artificial intelligence consisting of both Natural Language Processor and Diagnostic algorithm helps physicians in making diagnosis of complex cases. It helps in minimizing errors in diagnosis. Thus mis or missed cases are avoided and medical errors are minimized. There is potential for saving enormous costs in terms of loss of time and life by using ai-med for patient benefit.