Pns289 Evaluation of the Safety and Efficacy of Ai for Detection of Chronic Non-Communicable Diseases in Remote Areas

Abstract

CASP checklists. The success characteristics were extracted from the eligible articles. Results: The search returned with 1833 articles with 944 excluded for duplicates, non-relevance, study design and endpoints, and publication types after initial review. Preliminary result showed that diabetes, cardiology and obesity were the most common target disease areas for digital technology implementation. The most used digital technology were mobile applications, wearables, and web-based intervention, with artificial intelligence is increasingly studied. Publications on industry-sponsored trials, digital technology in clinical trials and as specific treatment companion are limited. The endpoints for outcome measurement and result of digital technology in improving patients' quality of care vary. The success factors for digital technology implementation are quality of care achievement (effective, efficient, accessible/ coverage, and standardized) and positive user experience (usability, acceptability, non-interference and reliability). Conclusions: Digital technology is increasingly used in healthcare settings and showed promising benefits to measure and improve patient outcome. Patients' insights, system standardization and validation are crucial for the success of digital solution. A standardized and robust study design is required to demonstrate the impact of digital technology on patients' quality of care.

Telemedicine Implementation Challenges in Underserved Areas of the Philippines

“…The challenge for telemedicine is to put emphasis on preventive medicine since the distance will no longer be a factor between patient and health professional. According to several studies, AI has been used in automatic screening of diabetic retinopathy [55], coordination and management of breast cancer [56], clinical deployment of prostate cancer diagnosis [57], detection and classification of chronic noncommunicable diseases [58], heart disease prediction [59], pneumonia detection [60], health screening [61], urinalysis examination [62], classification of skin diseases [63], and referral system [64] and voice controlled navigational aid [65] for visually impaired patients. Based on the studies, telemedicine can use AI for the purpose of diagnostics, communication of cure and medication, and monitoring of patients after surgery on the way to recovery or telerehabilitation after the pandemic [20], and before the pandemic [66].…”