According to Market and Market, the AI market will grow from $420 million in 2014 to $5.05 billion in 2020. Healhtcare industry is not an exception and actively implements the machine learning technologies. Gartner states that by 2018, there will be 6 billion wearable devices with an active use of AI. Just imagine how many wearable devices are there in the healthcare.


Moreover, healthcare is currently overwhelmed with chronic diseases. According to Center for Disease Control (CDC), the later account for $3 of every $4 spent for the healthcare purposes, that is $7900 for every American suffering from a chronic disease. Chronic disease is the reason for 7 out of ten deaths. But the good news is that chronic disease can be predicted and prevented. AI is a great tool for this.


AI has substantially improved big data analysis, for instance, Google’s Deepmind Health project. They incorporate clinicians, patients, and public involvement in their medical researches. They provide hospitals, their partners, with secure data services that share blockchain properties. IBM Watson for Oncology exploits patient’s data, clinical expertise, and external research to provide a personalized treatment.


It’s been reported that from 10 to 20 percent of cases are misdiagnosed yearly. It is a huge issue that can be solved with the help of AI. KenSci, a startup from Washington, believes that it can eliminate such troubles by identifying health risks patterns and defining high-risk ones by means of machine learning and big data analysis. Artificial Intelligence helps identify data&lt in large scopes of information and medical records increasing the efficiency of chronic disease medication treatment and enabling precision medicine. For instance, Atomwise launched a virtual search for the existing medicine to be redesigned to treat the Ebola virus.


Predictive Analytics: AI can analyze and predict stress and emotion response through image analysis via deep learning micro-expression analysis, like intonation analysis, voice stress, epilepsy seizure detection with the help of brain analysis, etc. Moorfields Eye Hospital in London collaborates with Deepmind to create an AI-driven system able of detecting sight-threatening conditions in digital scans of the eye.


Ai also improves chatbots and virtual assistants like Baidu’s medical chatbot, Melody, that is launched to make it easier to diagnose illnesses. It is integrated into the Baidu Doctor app that lets users contact doctors, schedule appointments, ask questions, etc.’s Molly helps users observe their chronic disease and generates personalized treatments.


AI can be also used to study the correlation of disturbance in earth’s magnetic field and solar activity with health. Linking probabilities between symptoms and conditions, AI can engage with the patients in the same way as clinicians.


Here is an interesting map of startups that operate in the sphere of healthcare AI provided by CBInsights

 ai healthcare startups

AI has an undeniable potential to bring healthcare to the next level and is actively proving it now.