Artificial Intelligence and Machine Learning’s impact on Clinical Diagnosis

Once far-flung technologies such as Artificial Intelligence, telehealth, Google glasses, blockchain, machine learning are now disrupting the way we deliver care. Patient experience is enhanced not only by collecting patient related data but by transforming that data into actionable insights. With 77% Americans having smart devices, and access to high-speed internet at home, health systems are becoming increasingly tech-savvy.

With EHRs, telehealth/telemedicine, population health systems now in place there is still a gap in health care delivery. Point of care is now gradually shifting from the hospital to smart homes. Majority of patients still face the problems of long wait times and high costs.

A patient visit usually has two outcomes, either it is critical or it could turn out to be the opposite. In both the cases people have to carve out a lot of time from their daily schedules to see a doctor. Here is where Artificial Intelligence and Machine Learning step in! Imagine the time, effort, and money that could be saved, having your symptoms analyzed without stepping out of your home or office?

Machine learning now isn’t just limited to board games; it is now used to check symptoms and diagnose potential issues before calling your physician. And it does this with greater precision as compared to searching your symptoms on the web.

With almost a third of healthcare AI SaaS companies focusing on diagnostics, there are tons of platforms available that expedite the diagnostics process using advanced algorithms to stimulate expert human reasoning. Typically machine learning diagnostic applications can be largely classified as AI-chatbots identifying patient’s symptoms and recommend appropriate course of action, or a rare disease being clinically diagnosed via face recognition software’s combined with machine learning.

 

Artificial Intelligence

 

Faichi Solutions has developed adaptive mobile platforms in the past connecting patients with providers instantaneously, facilitating asynchronous virtual visits, gathering data, storing and forwarding information between patients and primary care providers. It not only helps reduce the average wait times but also addresses the shortage of primary care physicians.

Potentially AI in healthcare could even predict future illnesses even before they manifest, improving the quality of services for patients.

Artificial Intelligence
Machine Learning
Clinical Diagnosis
Symptom Checker
Chatbots
healthcare

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