Artificial intelligence (AI) and machine learning (ML) are accelerating the domain of activities along with tons of possibilities for a range of industries, including biomedical research and healthcare delivery.
But are we really gaining out of it or simply losing control of our own steering? Do we need to be cautious for avoiding any harmful or devastating consequence? What is/are your opinion and future predictions?
Artificial intelligence is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent breakthroughs in AI technologies and their biomedical applications, identify the challenges for further progress in medical AI systems, and summarize the economic, legal and social implications of AI in healthcare.
Artificial intelligence is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent breakthroughs in AI technologies and their biomedical applications, identify the challenges for further progress in medical AI systems, and summarize the economic, legal and social implications of AI in healthcare.
AI and Machine Learning could be used as predictive, prescriptive, descriptive analytics tool for biomedical research.
Artificial Intelligence has the potential to not only be a successful equivalent alternative to 'human intervention/involvement", but also to surpass human expertise in certain aspects of biomedical research. For example, considering the context of time, unsupervised learning algorithms applied on medical images for image segmentation can be astronomically faster than segmenting medical images manually.
Indeed, with the arrival of machine learning and the need for quick, efficient and accurate healthcare services across the globe, biomedical research is indeed at the forefront of applying ML in its own domain and context.
ML based biomedical systems and products can pose certain risks. For example, a study employing a specific method to obtain 98% test accuracy might be used in an industry level product, but it may fail to obtain 98% accuracy in reality because the training and testing samples did not represent the true distribution of the population. Thus, like any medical product, ML based biomedical systems and products must go through rigorous tests, such as drug trials. Organizations/institutions must be formed which will govern, test and evaluate these products. Strict standardization of rules on medical products has always been prevalent, so why should ML based products be given a free ticket?
Thank you @M. A. A. Al- Fatlawi,@Rajani S Kamath and @Nahian Ahmed for your beautiful inputs.
The AI is based on the еру logical rule of implication (if ... then). AI created by humans will not contain rules that lead to devastating consequences.
We are certainly gaining out of it and can further benefits are endless but limited by our imaginations only. Like any other technology revolutions in the past this one too is carrying a baggage of uncertainties, negative implications and too much of hype or expectations.
To me the AI is as good or bad as we can enable it. As far as the biomedical research is concerned, I think it can certainly help us in achieving some of the results quicker & intelligently but it can certainly not replace the entire research work. I'm considering AI a one step above the computations (i.e. computers) where some decisions based on pre-defined complex logics & related pattern is taken automatically to reach some conclusions and it is up to us to decide if we want to further automate the follow up actions or intervene with human intelligence?
In case of health care I don’t think we have understood this area i.e. human body completely yet. No doubt, we have achieved a huge success in this field but still haven’t been able to understand it completely yet. You cannot manage what you cannot measure and we haven’t been able to convert this area into mathematics yet. As an example, no two patient respond back with same stats i.e. time of recovery, micro level impact of medicines on other areas, post recovery pattern etc.
I’m not from medical field so cannot go beyond this but I would be scared to let AI take a complete control of my medical issues. Yes, I would encourage AI on initial checks, lab testing, reporting, health predictions & recommendations etc. this is one area where AI can play a vital role in the preventive healthcare sector but I would be scared to let AI take a call on my surgery or prescribing serious medicines etc.
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