AI inspired healthcare is aiming at providing better care. From examining different computerized algorithms to matching behavior of complex medical data, the end objective is to optimize clinical procedures and clinical outcomes.
Lets check the stats of growth of AI in current healthcare space. AI in healthcare is growing with a CAGR of 14% and is expected to be a market of $35B by 2025. Revenue!! Profit!! Growth!! is what each business seeks whether a startup or an established enterprise. Here are some of the potential areas of growth you can leverage from based on our analysis of market in 2018 are:-
1. Radiology Image Analysis: Currently, image analysis is very time consuming for human providers, with use of machine-learning algorithm you can analyze 3D scans upto 90-95% faster then manual. Additionally, AI image analysis can support remote areas that don’t have easy access to healthcare providers and make tele-medicine more effective as patients can use their camera phones to send in pics of rashes, bruises to determine what care is required. Google has launched new eye detection ML algorithm analyzing scans of the back of a patient’s eye to assess a person’s risk of heart disease using machine learning.
2. Virtual nursing assistants: Uniquely manages high volume patient engagement, like a digital nurse to help people monitor patient’s condition and follow up with treatments, between doctor visits. Care Angel’s virtual nurse assistant can even provide wellness checks through voice and AI. Based on the inputs, further commands to be sent to doctor or a doctor connect is required.
3. Clinical Trials: Finding an eligible patient for clinical trials is always very tedious and cumbersome process for research organizations because it takes days to find out whether the patient is eligible for trials or not but with the help of AI you can easily reduce the trials time by almost half, improving trial quality. AI is finding bio-markers and gene signatures that cause diseases, recruiting eligible clinical trial patients in minutes, reading volumes of text in seconds.
4. Dosage Errors: With the help of AI by defining algorithms on extensive data available, you can determine the correct dosage to be suggested to patients which improvises the overall process by 30-40%. This is very effective for patients taking immuno suppressant drugs to administer to organ patients
5. Health Monitoring : Wearable health trackers – like FitBit, Apple, Garmin – monitors heart rate and activity levels. With AI, there will be alerts to the user to get more exercise and can share this information to doctors for additional data points on the needs and habits of patients.
6. AI assisted Robotic Surgery: With AI techniques, you can analyze data from pre-op medical records to physically guide the surgeon’s instrument in real-time during a procedure. Eventually which can reduction by 21% in patients’ length of stay in the hospital following surgery.
7. Healthcare Fraud Detection: Predictive analytics identifies patterns that are potentially fraudulent and then develops sets of “rules” to “flag” certain claims. Generally, healthcare frauds are not obvious and thus difficult to detect. The “intelligence” in the system learns from these new rules and continually becomes more sophisticated in identifying, even more, fraud potentials.
Technology turn advantageous when implemented with adequate R&D in the niche you are operating in. This is what we are doing and advice the same, “Probing towards smartHealth.”