AI Medical Compendium Journal:
Frontiers in digital health

Showing 21 to 30 of 33 articles

Identifying Heart Failure in ECG Data With Artificial Intelligence-A Meta-Analysis.

Frontiers in digital health
Electrocardiography (ECG) is a quick and easily accessible method for diagnosis and screening of cardiovascular diseases including heart failure (HF). Artificial intelligence (AI) can be used for semi-automated ECG analysis. The aim of this evaluati...

Adaptive Physics-Based Non-Rigid Registration for Immersive Image-Guided Neuronavigation Systems.

Frontiers in digital health
In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, parti...

Telemedicine in Arab Countries: Innovation, Research Trends, and Way Forward.

Frontiers in digital health
The progress and innovation in telemedicine within the Middle Eastern countries have not been heavily monitored. Therefore, the present study aims to analyze the scholarly work conducted in the Arab world, using reproducible statistical and scientom...

Machine Learning Revealed New Correlates of Chronic Pelvic Pain in Women.

Frontiers in digital health
Chronic pelvic pain affects one in seven women worldwide, and there is an urgent need to reduce its associated significant costs and to improve women's health. There are many correlated factors associated with chronic pelvic pain (CPP), and analyzing...

Harmonization of the ICHOM Quality Measures to Enable Health Outcomes Measurement in Multimorbid Patients.

Frontiers in digital health
To update the sets of patient-centric outcomes measures ("standard-sets") developed by the not-for-profit organization ICHOM to become more readily applicable in patients with multimorbidity and to facilitate their implementation in health informati...

Predicting Common Audiological Functional Parameters (CAFPAs) as Interpretable Intermediate Representation in a Clinical Decision-Support System for Audiology.

Frontiers in digital health
The application of machine learning for the development of clinical decision-support systems in audiology provides the potential to improve the objectivity and precision of clinical experts' diagnostic decisions. However, for successful clinical appl...

Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models.

Frontiers in digital health
AI-driven digital health tools often rely on estimates of disease incidence or prevalence, but obtaining these estimates is costly and time-consuming. We explored the use of machine learning models that leverage contextual information about diseases...

The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation.

Frontiers in digital health
Although many clinical metrics are associated with proximity to decompensation in heart failure (HF), none are individually accurate enough to risk-stratify HF patients on a patient-by-patient basis. The dire consequences of this inaccuracy in risk ...

Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes.

Frontiers in digital health
Artificial intelligence (AI) digital health systems have drawn much attention over the last decade. However, their implementation into medical practice occurs at a much slower pace than expected. This paper reviews some of the achievements of first-g...

Evolution of Wearable Devices in Health Coaching: Challenges and Opportunities.

Frontiers in digital health
Wearable devices hold an enormous potential in contributing to an improved global health. The availability, non-invasiveness, and affordability of those systems make them promising candidates to transform the standard of care for health coaching. The...