Manifesting 'AI Utopia' in Healthcare Industry

By Healthcare Tech Outlook | Tuesday, December 11, 2018

The healthcare industry is always receptive to technological innovations because it deals with a huge amount of data on daily basis. Medical histories, patient information, clinical studies, diagnostic results, hospital billing are the few data sources available in the healthcare sector. There is a lot of excitement about how Artificial Intelligence (AI) is changing the industry.

Here are the most potential AI advances in healthcare

1. Ability in aiding people in maintaining health:

The internet of medical things (IoMT) application is providing healthcare application in nurturing a healthy lifestyle and behavior. Wearable medical health (mHealth) devices better illustrate this. It can send alerts to caregivers. There is a practice of monitoring patients in their home with the help of IoMT devices known as telemedicine.

2. AI-assisted robotic surgery:

AI enabled robots are increasingly assisting in surgical procedures. It helps the surgeon perform better. These insights can link to the patient's postoperative health outcomes. The only thing that might hinder the growth is the cost of the equipment. For now, they are fantastic assistants reducing the variability of outcomes.

3. Clinical judgment diagnosis:

AI is playing a crucial role in detecting diseases. The diagnostic applications fall under the categories of chatbots, oncology, pathology, and rare diseases. AI chatbots use speech recognition capability to identify patterns in patient symptoms and then diagnosing. It arguments preventing diseases and appropriate course of action. In oncology, researchers are developing algorithms to detect cancerous tissues. Pathology diagnosis a disease based on laboratory analysis of body fluids. Machine learning can enhance the efforts of pathologies who are only left with microscopes. Facial recognition software combined with machine learning is developing to help clinicians in diagnosing. In facial analysis deep learning is used to phenotypes that correlate with rare genetic diseases.

4. Precision medicine:

Using AI to develop precision healthcare can assist physicians and researchers in predicting treatments and prevention strategies. Here AI is used to identify patterns within high volume genome data sets. The models built from these data sets help in identifying affected genes and predicting the probability of developing certain diseases for a sub-group of people or an individual.

5. Drug discovery:

Biopharmaceutical companies are using machine learning to power its search for drugs. Companies like Sanofi, Genentech, Pfizer are beginning to build the partnership with AI service providers. Causes for many previously unknown diseases can ALSO be pinpointed with the help of AI.

But there is still much to overcome to achieve an efficient AI dependent healthcare. Data privacy issues and data mismanagement are some of the major concerns. But if the providers can offer a responsible handling of data, AI can unimaginably revolutionize the whole healthcare industry.

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