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How AI and ML are Transforming Healthcare

Artificial Intelligence (AI) and Machine Learning (ML) are with no doubt among the most transformative technologies of this century. Their uses continue to be explored across diverse industries. However, the two technologies present tremendous opportunities in the healthcare and medical fields.

How is AI and ML Transforming the Healthcare Industry?

Initially, healthcare technology was solely used to improve back-office operations. However, AI has a broad array of uses and is today a key enabler in improving healthcare outcomes. AI and ML are expediting the development of new models and the exploration of novel treatments.

1. Better Clinical Decisions

It’s critical that healthcare professionals take into consideration every piece of information when making a diagnosis. Hence they have to read through a host of structured and unstructured medical records before they can make an informed and accurate diagnosis. The slightest mistake can place the life of the patient at risk.

With the help of Natural Language Processing (NLP), medical professionals are now able to narrow down to the most pertinent patient information. With AI, large sets of data can be processed and stored hence providing knowledge databases that support clinical decisions.

2. Identifying Rare and Difficult to Diagnose Diseases

This primarily involves detecting the ‘edge-cases’. This machine learning system is built on large data sets with raw images and various transformations of the disease.

A perfect example is the Microsoft Project InnerEye that uses ML to categorize and identify tumors using 3D radiological images. It’s instrumental in precise surgery planning, navigation, and accurate tumor contouring for radiotherapy. MRI and more advanced medical imaging systems are also equipped with ML algorithms.

3. Surgical Assistance Robots

Both AI and ML promise to revolutionize medical surgical procedures with robotics. Thanks to machine learning and complex algorithms, AI can determine patterns in surgical procedures and provide unmatched precision. Robots have a superhuman ability to repeat exact motions and hence can create precise and minimally invasive incisions. They can also make use of the AI virtual reality space for real-time instruction and guidance. They also avail the possibility for remote surgery and telemedicine.

4. Drug Discovery

AI and ML are increasingly being used to facilitate successful drug discovery. This is for all therapeutic domains, including immuno-oncology, cancer treatments, and metabolic diseases. These technologies are being used to accelerate processes such as early-stage candidate selection and mechanism discovery.

5. Enhance Primary Care and Patient Experience

People have a tendency of booking an appointment with their doctor at the slightest hint of a symptom, yet sometimes it can be a false alarm. AI can play a critical role by automating primary care hence allowing doctors to concentrate on more pertinent issues.

AI-powered chatbots can help people save money by providing them with real-time answers to health-related queries. 24/7 chatbots can serve multiple patients simultaneously hence streamlining and improving primary health care.

6. Streamlining Claims Processing

Claims processing and reimbursement are core components of the healthcare revenue cycle. It involves many stakeholders and steps. Each phase is critical hence effective and accurate communication among all stakeholders is imperative. A majority of hospitals are using AI to streamline claims processing and reimbursement to optimize workflows and minimize errors.

Affordable and quality healthcare has been the subject for debate for the longest time. Personalized medicine, smart records, and outbreak prediction are other areas being explored by healthcare professionals. Though AI and associated data-driven technologies are revolutionizing healthcare, experts need to be extra vigilant since the deployment of novel and relatively untested technologies like the case of Epic’s Deterioration Index may result to biases and a host of other issues.

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