AI In Healthcare: Prevention, Diagnostics and Treatment Big Cloud Recruitment

AI, the impact of which is simultaneously over-hyped and under-rated in most sectors, is catalyzing revolutionary use cases in healthcare. Deep learning has come a long way from identifying cats and dogs and can now perform independent image-based diagnosis with comparable or better accuracy than (human) doctors. X-Ray or scan-based diagnosis of tumours, fractures, strokes, electrodiagnosis can be entirely done by algorithms. While several of these options have received FDA approval and starting a clinical trial or beginning to be used in production, researchers are attempting selfie diagnosis to detect 50 diseases from abnormalities in eye colour (Nature,2018) and diagnosis from (molecules emitted from) body odour. Using data from wearables or behavioural observations such as changes in gait, driving patterns, mouse usage etc., machine learning algorithms can predict the onset of physiological (particularly neurological or cardiovascular) or psychiatric disorders, assist management of chronic conditions such as diabetes or epilepsy, and even raise real-time warnings.