10 Promising AI Applications In Health Care

The list below is incomplete. However, it provides an insight on some of the impacts of Machine Learning in the healthcare industry.

1. Diagnosis in Medical Imaging:

Computer vision has been one of the most remarkable breakthroughs, thanks to machine learning and deep learning, and it is a particularly active healthcare application for machine learning.

Courtesy: BBC Know

2. Diagnostic Applications:

Deep learning can in all probability play a lot of necessary roles in diagnostic applications as deep learning becomes more accessible, and as a lot of information sources (including rich and varied kinds of medical imagery) become a part of the AI diagnostic method.

3. Treatment Queries and Suggestions:

Diagnosis is a terribly sophisticated method, and involves – at least for now – a myriad factors (everything from the colour of whites of a patient’s eyes to the food they need for breakfast) of which machines cannot presently collate and create sense; but, there is very little doubt that a machine may aid in serving physicians to create the proper considerations in diagnosing and treatment, just by serving as an associate extension of knowledge base.

4. Scaled Up / Crowdsourced Medical Data Collection:

There is a great deal of focus on pooling data from various mobile devices in order to aggregate and make sense of more live health data.

5. Drug Discovery:

While much of the healthcare trade may be a bog of laws and crisscrossing incentives of assorted stakeholders (hospital CEOs, doctors, nurses, patients, insurance firms, etc.), drug discovery stands out as a comparatively simple quantity for machine learning healthcare application creators.

6. Robotic Surgery:

The da Vinci robot has attracted major attention in the robotic surgery space and a few might argue, for good reason. This device permits surgeons to control dextrous robotic limbs so as to perform surgeries with fine detail and in tight areas (and with fewer tremors) than would be doable by the human hand alone.

Courtesy: The Da Vinci Bot

Future Applications:

7. Personalized Medicine:

Personalized medicine promises a world of customized drugs within which everyone’s health recommendations and disease treatments are tailored, based on their medical record, genetic lineage, past conditions, diet, stress levels and more.

8. Automatic Treatment or Recommendation:

In the diabetes campaign by Medtronic and IBM, Medtronic’s own Hooman Hakami states that at some point, Medtronic wants to have their insulin checking pumps work autonomously, monitoring blood-glucose levels and injecting insulin as needed, without disturbing the user’s daily life.

9. Improving Performance (Beyond Amelioration):

One can imagine that disease prevention or athletic performance will not be the only health-promoting apps. Machine learning may be implemented to track worker performance or stress levels on the job, as well as for seeking positive improvements in at-risk groups (not just relieving symptoms or healing after setbacks).

10. Autonomous Robotic Surgery:

At present, robots like the da Vinci are largely an extension of the dexterity and trained ability of an operating surgeon. In the future, machine learning might be used to mix visual information and motor patterns within devices such as the da Vinci in order to permit machines to master surgeries.


Diagnosis, treatment and prevention are all huge problems that are based in part on plentiful data, and their improvement represents incalculable value not to mention a great service to the mankind at large.



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