The technology development of machine learning in healthcare assists various medical issues and it also enhances treatment for all diseases.
FORMA, CA: The healthcare industry offers value-based care to millions of people and it is becoming a top revenue generator for many countries. Machine Learning is already lending a hand in various use cases in healthcare. Technology development in the world today is helping in various medical fields. Machine learning is one such technology that is witnessing gradual acceptance in the healthcare industry. Google has identified a new algorithm recently to operate on cancer tumours in mammograms, and researchers at Stanford University are using deep learning to identify the treatment for skin cancer.
The rise of various applications of machine learning is reaching a global level allowing for backup future data, analysis, innovative work etc. It also increases the efficacy of new treatments which was nearly impossible before. There are few applications of machine learning in healthcare which would help to diagnose genetic diseases.
One of the chief ML applications in healthcare is the identification and diagnosis of diseases and ailments which are otherwise considered hard to diagnose. This can include anything from cancers–which are tough to catch during the initial stages–to other genetic diseases. IBM Watson Genomics is an example of how integrating cognitive computing with genome-based tumour sequencing can help in making a fast diagnosis. Berg, the biopharma giant, is leveraging AI to develop treatments in areas such as oncology. Predicting Response to Depression Treatment aims to develop a commercially feasible way to diagnose and provide treatment in routine clinical conditions.
One of the primary clinical applications of machine learning lies in the early-stage drug discovery process. This also includes R&D technologies such as next-generation sequencing and precision medicine which can help in finding alternative paths for therapy of multifactorial diseases. Currently, ML techniques involve individually learning which can identify patterns in data without providing any predictions. Project Hanover developed by Microsoft is using ML-based technologies for multiple initiatives including developing AI-based technology for cancer treatment and personalising drug combinations for Acute Myeloid Leukaemia.
Machine learning and deep learning are both responsible for the breakthrough technology called Computer Vision. This has found acceptance in the Inner Eye initiative developed by Microsoft which works on image diagnostic tools for image analysis. As machine learning becomes more attainable and as they grow in their illustrative capacity, expect to see more data sources from varied medical imagery become a part of this AI-driven diagnostic process. Behavioural modification is an important part of preventive medicine, and ever since the propagation of machine learning in healthcare countless startups are evolving in the fields of cancer prevention and identification, patient treatment, and more.