Throughout history, attempts have been made to make medicine more accurate, non-invasive, and treatable.With the emergence of Intelligent Medical Technologies we aim to analyse if the expanding AI industry offers any benefits in clinical healthcare.

We've progressed from traditional equipment like implants, stents, and SpO2 monitors to wearables,biosensors and other computer-aided diagnostic gadgets.Facial recognition in customised dermatological treatments is already being employed by beauty and wellness enterprises.Medical Screening is a major application of AI enabled algorithms.

Intelligent Algorithms

An algorithm learns to be intelligent by feeding it data for which we already have answers too.For example, a number of MRI scanned pictures are provided to detect a clot.Based on this, the algorithm is taught to provide more accurate results if clot presence is predictable in future scans.Such tasks involving huge amounts of data and medical detection can be accurately performed by AI.

Recent Applications

DLAD

Deep Learning Based Automatic Detection was developed using forty three thousand chest radiographs of a variety of patients which were annotated by certified radiologists.DLAD showed a higher performance than the physicians and also improved nodule detection and enhanced performance as a second reader.

Glucose Sensor

A fourth generation subcutaneous was tested on 88 subjects.They wore two sensors in the abdomen paired with an insulin pump and a third sensor on the arm connected to the glucose sensor.The Guardian Glucose sensor provided accurate readings as compared to the YSI reference values for the 7-day period.

Gastroenterology

Early Neoplasia in Barrett's oesophagus is difficult to diagnose and 100 images from 44 subjects were taken for the same.The system identified early neoplastic lesions by image analysis with reasonable accuracy suggesting that automated detections are possible.

Regulations

Recent AI algorithms in the health business forecast an improvement in our quality of life.

However, most AI algorithms are not created by doctors who treat patients.Patients also may be sceptical about computerised diagnosis fearing misleading cases.Unlike generative AI, medical technologies have received little attention and require more awareness and financial backing.This calls for an updated curriculum in medical schools that will equip future doctors with a wide range of skills such as programming,AI,ML and automation.

Clinical practices very soon will be completely automated which will help in better patient load management, improved time management and adequate distribution of medical resources.

Harvard University Frontiers Medicine Publication Pub Med Image from Middle East Medical Portal