Artificial Intelligence
Leveraging AI, machine learning and neural networks can help healthcare standardize data, comply with info blocking requirements and improve health outcomes.
Grace Chang, cofounder and CEO of Kintsugi, explains how clinicians can identify signs of clinical depression and anxiety in everyday health conversations with the use of voice biomarker technology and machine learning assessments.
Also, Singapore's Minister for Health Ong Ye Kung is participating in a new large-scale population health study.
LA Children's received the funding to predict how critically ill children handle medication by applying machine learning to identify clinically significant patterns from the ICU data of 20,000 patients.
Also, AIIMS will start requiring teleconsultations for follow-ups next year.
Resource constraints and inefficient manual processes are burdening cancer centers across the U.S., but a new report shows how machine learning capabilities outside of EHRs could help improve agility.
A natural language processing expert explains why he feels the technology's kinks have been ironed out, its ROI has been proven and the timing is right for healthcare to take advantage of information-extraction tools.
In this special episode, recorded live in Boston at the HIMSS Healthcare Cybersecurity Forum, Roshal Marshall of McKesson discusses this and other issues, including AI integrity and information blocking rule compliance.
These advanced technologies will do more to help provider organizations with workflow optimization, staff shortages and the patient experience in the year ahead, one expert predicts.
Also, the Japanese government is conducting a study to deploy an AI endoscopy diagnosis support tool in Vietnam.