- 期刊
Early Detection of Cancer using Non-invasive Machine Learning: A Survey of Technologies
摘要
Machine Learning algorithms have been proven helpful in solving complex healthcare problems in the last few decades and forged the recent advancements in mHealth and Healthcare Informatics research. In particular, the Machine Learning-based non-invasive monitoring and assessment of health biomarkers have gained traction in the scientific community. mHealth tools fueled with Machine Learning models are accurate, cheaper, pain and trauma-free, and can provide on-the-fly assessment; hence they can be an excellent solution for early assessment of diseases. This paper will explore different avenues of research encompassing Machine Learning- based non-invasive and early cancer detection. As this particular domain of research is in an embryonic stage, a critical literature review of the papers published to date will be helpful for prospective researchers to get a holistic view before they delve into the advancements. We encapsulate the techniques, scopes, challenges, and limitations and critically comment on the roadblocks ahead.