The digital health space refers to the integration of technology and health care services to improve the overall quality of health care delivery. It encompasses a wide range of innovative and emerging technologies such as wearables, telehealth, artificial intelligence, mobile health, and electronic health records (EHRs). The digital health space offers numerous benefits such as improved patient outcomes, increased access to health care, reduced costs, and improved communication and collaboration between patients and health care providers. For example, patients can now monitor their vital signs such as blood pressure and glucose levels from home using wearable devices and share the data with their doctors in real-time. Telehealth technology allows patients to consult with their health care providers remotely without having to travel to the hospital, making health care more accessible, particularly in remote or rural areas. Artificial intelligence can be used to analyze vast amounts of patient data to identify patterns, predict outcomes, and provide personalized treatment recommendations. Overall, the digital health space is rapidly evolving, and the integration of technology in health

Sunday, November 29, 2020

Artificial Intelligence for the Health Community: Don't leave Home without It


Today all physicians need to know about artificial intelligence, such as deep learning, machine learning, image processing and analytics.  Few health providers know much about artificial intelligence, and for clinicians there is little need to know the details, other than to select a ready made solution out of the box, downloadable from the interweb.  A.I. is developing rapidly and is undergoing rapid adoption by hospitals, clinics and some providers.

IBM Watson and MD Anderson Cancer entered into a joint venture for treatment of cancers.  The effort failed because neither partner quite knew what AI was not capable of accomplishing at this early iteration.  There is a learning curve that takes substantial time.  The algorithms must be written and then instructed with experience.  Each step adds to the database making the application smarter. 

This edition of Digital Health Space will attempt to guide the  learner in acquiring some skills in using artificial intelligence, and to take a look 'under the hood'.  Few practitioners will have time or resources to learn programming and/or machine learning.  

Despite what you may hear AI is not for the average provider. It has become a buzzword, and using the word loosely announces true ignorance of the tool. 

Anyone serious about AI should start with a skill set in programming, systems and computer languages. If you are interested in medicine acquiring this skill in undergraduate and/or graduate education will bring a powerful tool to medical practice, and research.  

A.I. is being applied in genomics, proteomics, cardiology, imaging, neural networks and about every basic science or clinical specialty.  Natural language processing as demonstrated in Siri, Alexa and Nuance is one example of artificial intelligence




One must have a clear vision of what you want to accomplish.  It will nor replace physicians. It may increase efficiency, decrease errors, and allow for more cost effective medicine.  It has application for health insurance, health policy, epidemiology, and predictive analytics.  It may be the alphabet soup of intelligence. 

The accompanying information allows the reader to review educational courses and determine what would be appropriate for their need.

Every decade or so there is a technological tsunami that transforms multiple industries.

Artificial Intelligence (AI) is that wave sweeping the technology world today. If you want to join this revolution but do not have the skills yet, this series of courses are right for you.

OpenCV.org supports the largest computer vision library in the world. We are on a mission to create the most comprehensive online courses in AI to educate a global workforce.

These courses are designed for Working Professionals and Students alike. The only prerequisite for taking these courses is a basic understanding of Python or C++.

The courses require 3-4 months to complete if you commit 5-8hrs/week for learning.


Certification is available for the course(s)











(20) AI courses by OpenCV

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