Psychiatry in the digital age: A blessing or a curse?
CB Roth, A Papassotiropoulos, AB Brühl… - International journal of …, 2021 - mdpi.com
Social distancing and the shortage of healthcare professionals during the COVID-19
pandemic, the impact of population aging on the healthcare system, as well as the rapid …
pandemic, the impact of population aging on the healthcare system, as well as the rapid …
Ketamine use disorder: preclinical, clinical, and neuroimaging evidence to support proposed mechanisms of actions
Ketamine, a noncompetitive N-methyl-D-aspartate (NMDA) receptor antagonist, has been
exclusively used as an anesthetic in medicine and has led to new insights into the …
exclusively used as an anesthetic in medicine and has led to new insights into the …
Computational intelligence-based classification system for the diagnosis of memory impairment in psychoactive substance users
C Zhu - Journal of Cloud Computing, 2024 - Springer
Computational intelligence techniques have emerged as a promising approach for
diagnosing various medical conditions, including memory impairment. Increased abuse of …
diagnosing various medical conditions, including memory impairment. Increased abuse of …
Opioid death projections with AI-based forecasts using social media language
Targeting of location-specific aid for the US opioid epidemic is difficult due to our inability to
accurately predict changes in opioid mortality across heterogeneous communities. AI-based …
accurately predict changes in opioid mortality across heterogeneous communities. AI-based …
Use of machine learning to examine disparities in completion of substance use disorder treatment
The objective of this work is to examine disparities in the completion of substance use
disorder treatment in the US Our data is from the Treatment Episode Dataset Discharge …
disorder treatment in the US Our data is from the Treatment Episode Dataset Discharge …
White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working …
Background Nicotine and illicit stimulants are very addictive substances. Although
associations between grey matter and dependence on stimulants have been frequently …
associations between grey matter and dependence on stimulants have been frequently …
[HTML][HTML] The adverse effects and nonmedical use of methylphenidate before and after the outbreak of Covid-19: Machine learning analysis
Background Methylphenidate is an effective first-line treatment for attention-
deficit/hyperactivity disorder (ADHD). However, many adverse effects of methylphenidate …
deficit/hyperactivity disorder (ADHD). However, many adverse effects of methylphenidate …
Binge eating, purging, and restriction symptoms: Increasing accuracy of prediction using machine learning
Eating disorders are severe mental illnesses characterized by the hallmark behaviors of
binge eating, restriction, and purging. These disordered eating behaviors carry extreme …
binge eating, restriction, and purging. These disordered eating behaviors carry extreme …
Predicting US county opioid poisoning mortality from multi-modal social media and psychological self-report data
Opioid poisoning mortality is a substantial public health crisis in the United States, with
opioids involved in approximately 75% of the nearly 1 million drug related deaths since …
opioids involved in approximately 75% of the nearly 1 million drug related deaths since …
Practical foundations of machine learning for addiction research. Part I. Methods and techniques
P Cresta Morgado, M Carusso… - The American Journal …, 2022 - Taylor & Francis
Machine learning assembles a broad set of methods and techniques to solve a wide range
of problems, such as identifying individuals with substance use disorders (SUD), finding …
of problems, such as identifying individuals with substance use disorders (SUD), finding …