By Aman Dheer
The advent of Machine Learning (ML) and Artificial Intelligence (AI) has revolutionized the massive healthcare sector piece-by-piece and has shed light on the intertwining of technology and health as a single unit. Mankind faces numerous healthcare challenges ranging from complicated diseases such as Cancer to rapidly mutating infections and all of these can be improved and made more efficient with the help of technology.
ML and AI can help streamline the process of mapping infections, treating diseases and smoothing the administrative processes in hospitals and clinics. It can be used by doctors and healthcare professionals to figure out various routes of treatment and prescribe the correct doses of medications without any human error or misunderstanding. It can even be used to advise patients on various surgical and treatment options in consideration of risk factors and complications that may arise.
Below is a list of various types of technologies under AI/ML that are being used commonly in the healthcare sector:
- Neural networks and deep learning: Neural networks and deep learning utilize various levels and models that can help in the mapping of predictable treatment models by scanning various features. For example, X-rays can be analysed by an AI/ML software to determine type of fracture and specify the appropriate treatment and duration time for it or Berg(a bio-pharma giant) has been using AI to develop oncology treatments.
- Natural Language Processing: Natural Language Processing(NLP) can help develop text-analysis and speech recognition in order to make sense of the human language.
- Rule-based expert systems: Rule-based systems(if/else) can help doctors and professionals make proper clinical decisions while diagnosing a patient.
- Physical Robots: Physical robots and machines can help in automation of various surgical & therapeutic procedures. Robots are currently being used in stitching wounds, making invasive incisions and even in eye-surgeries.
- Robotic Process Automation: Robotic Process Automation can help clinics and hospitals arrange, add, analyse and estimate the treatment costs for patients. They can even arrange patient records accordingly, for better management of the system and to ensure the timely treatment of patients. We have seen MATLAB’s machine learning-based handwriting recognition technology help arrange clinical records based on numerous filters and parameters.
- Outbreak prevention: AI/ML allow scientists to access large amounts of data and use them to predict outbreaks of severe chronic and infectious diseases. These are extremely useful for third-world countries and for regions with under-funded medical infrastructure. ProMED-mail is an internet based reporting platform which monitors evolving diseases and reports outbreaks in real-time.
Various AI/ML companies have made numerous strides in the healthcare market and have introduced products that are efficient and consumer-friendly. Some of them include-
- PathAI, a company which uses Machine Learning to assist pathologists in making accurate diagnosis and develop methods for medical treatment.
- Enlitic, a San-Francisco based company that utilizes deep-learning to analyse blood tests, genomics, radiology images etc., and give better insight into the patient’s condition and treatment needs.
- Berg Health, an organisation which strives to use Artificial intelligence to find links.
- Microsoft’s Azure, which is a machine learning initiative is being used by companies such as Airdoc to scan the eye for abnormalities and vision-defects.
These are just a few noteworthy accounts in the long list of organisations and companies that have dedicated themselves to achieving a fitting between healthcare and AI/ML.
While AI/ML has a variety of applications and benefits for the healthcare sector, it comes with its own set of disadvantages. Machine errors can hamper treatments/diagnosis and can put the patient’s life at risk. It can even reduce the human workforce leading to elimination of jobs.
