[HTML][HTML] A systematic review of machine learning models in mental health analysis based on multi-channel multi-modal biometric signals

J Ehiabhi, H Wang - BioMedInformatics, 2023 - mdpi.com
With the increase in biosensors and data collection devices in the healthcare industry,
artificial intelligence and machine learning have attracted much attention in recent years. In …

AI and Big Data for Therapeutic Strategies in Psychiatry

S Guggari - Trends of Artificial Intelligence and Big Data for E …, 2023 - Springer
Psychiatric illnesses are well known in the research community through scientific findings in
the past few decades. The detection and treatment of psychiatric diseases are unsatisfactory …

[HTML][HTML] The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers

E Gliwska, K Barańska, S Maćkowska, A Różańska… - Cancers, 2023 - mdpi.com
Simple Summary Psychological assessment of a cancer patient is a challenge due to the
difficulty of the issues raised and, additionally, the lack of a sufficient number of psycho …

Smartening E-therapy using Facial Expressions and Deep Learning

HB Vadapalli - 2020 2nd International Multidisciplinary …, 2020 - ieeexplore.ieee.org
Emotional intelligence finds its application in several fields, and researchers are currently
looking to explore the possibility for computers to demonstrate such intelligence. Examining …

Extracting Complementary and Integrative Health Approaches in Electronic Health Records

H Zhou, G Silverman, Z Niu, J Silverman… - Journal of Healthcare …, 2023 - Springer
Abstract Complementary and Integrative Health (CIH) has gained increasing popularity in
the past decades. While the evidence bases to support them are growing, there is still a gap …

[HTML][HTML] A novel method for classifying body mass index on the basis of speech signals for future clinical applications: a pilot study

BJ Lee, B Ku, JS Jang, JY Kim - Evidence-Based Complementary …, 2013 - hindawi.com
Obesity is a serious public health problem because of the risk factors for diseases and
psychological problems. The focus of this study is to diagnose the patient BMI (body mass …

Augmenting mental healthcare with artificial intelligence, machine learning, and challenges in telemedicine

S Avasthi, T Sanwal, P Sareen… - Handbook of Research on …, 2022 - igi-global.com
Artificial intelligence is a huge part of the healthcare industry, having applications and uses
in oncology, cardiology, dermatology, and many other fields. Another area where AI is …

[PDF][PDF] Explainable AI (XAI) Applied in Machine Learning for Pain Modeling: A Review. Technologies 2022, 10, 74

R Madanu, MF Abbod, FJ Hsiao, WT Chen, JS Shieh - 2022 - academia.edu
Pain is a complex term that describes various sensations that create discomfort in various
ways or types inside the human body. Generally, pain has consequences that range from …

[HTML][HTML] Analysis of patient cues in asynchronous health interactions: pilot study combining empathy appraisal and systemic functional linguistics

ER Velasco, HS Pedersen, T Skinner - JMIR formative research, 2022 - formative.jmir.org
Background: Lifestyle-related diseases are among the leading causes of death and
disability. Their rapid increase worldwide has called for low-cost, scalable solutions to …

[HTML][HTML] On how chronic conditions affect the patient-AI interaction: A literature review

M Tahri Sqalli, D Al-Thani - Healthcare, 2020 - mdpi.com
Background: Across the globe, managing chronic diseases has been recognized as a
challenge for patients and healthcare providers. The state of the art in managing chronic …