The application of machine learning techniques in posttraumatic stress disorder: a systematic review and meta-analysis

npj Digital Medicine, Journal Year: 2024, Volume and Issue: 7(1)

Published: May 9, 2024

Abstract Posttraumatic stress disorder (PTSD) recently becomes one of the most important mental health concerns. However, no previous study has comprehensively reviewed application big data and machine learning (ML) techniques in PTSD. We found 873 studies meet inclusion criteria a total 31 those sample 210,001 were included quantitative analysis. ML algorithms able to discriminate PTSD with an overall accuracy 0.89. Pooled estimates classification from multi-dimensional (0.96) are higher than single types (0.86 0.90). can effectively classify models using perform better types. While selecting optimal combinations be clinically applied at individual level still remains challenge, these findings provide insights into classification, identification, diagnosis treatment

Language: Английский

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An Empirical Analysis of Multimodal Affective Computing Approaches for Advancing Emotional Intelligence in Artificial Intelligence for Healthcare

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 114416 - 114434

Published: Jan. 1, 2024

Language: Английский

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Bimodal Self-Esteem Recognition: A Multi-Scenario Approach Based on Psychology

Published: Jan. 1, 2025

Language: Английский

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Modality independent federated multimodal classification system detached EEG, audio and text data for IID and non-IID conditions

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 108, P. 107938 - 107938

Published: April 24, 2025

Language: Английский

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Enhanced electrochemical oxidation and machine learning-assisted sensing of tetrabromobisphenol A using activated carbon facilitated CoWO4 heterostructures

Materials Science and Engineering B, Journal Year: 2024, Volume and Issue: 308, P. 117546 - 117546

Published: July 10, 2024

Language: Английский

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Current Applications of Artificial Intelligence in Psychiatry

Scientia. Technology, science and society., Journal Year: 2025, Volume and Issue: 2(4), P. 125 - 143

Published: April 1, 2025

The integration of artificial intelligence (AI) into psychiatric practice has accelerated rapidly, driven by advances in computational methods and the availability diverse data sources. present paper examines contemporary AI applications across diagnostic support, predictive analytics, therapeutic interventions, digital phenotyping, telepsychiatry integration, ethical, legal, social considerations. Foundations machine learning, deep natural language processing are delineated alongside relevant modalities, including structured clinical records, unstructured notes, multimodal signals. roles symptom detection, neuroimaging pattern recognition, biomarker discovery, differential diagnosis evaluated. Predictive models for suicide risk, relapse, treatment response reviewed, with attention to personalization algorithms. Therapeutic tools, such as conversational agents, virtual reality, gamified mobile applications, discussed. Passive monitoring techniques, workflows, clinician dashboards described. Ethical challenges, privacy, algorithmic bias, regulatory frameworks, considered. Implementation barriers adoption factors analyzed. Emerging trends, federated fusion, explainable AI, low-resource settings, explored. Implications patient outcomes, health systems, policy synthesized, concluding recommendations future research practice.

Language: Английский

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Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e2217 - e2217

Published: July 29, 2024

As the pandemic continues to pose challenges global public health, developing effective predictive models has become an urgent research topic. This study aims explore application of multi-objective optimization methods in selecting infectious disease prediction and evaluate their impact on improving accuracy, generalizability, computational efficiency. In this study, NSGA-II algorithm was used compare selected by with those traditional single-objective optimization. The results indicate that decision tree (DT) extreme gradient boosting regressor (XGBoost) through outperform other terms Compared ridge regression model methods, XGBoost demonstrate significantly lower root mean square error (RMSE) real datasets. finding highlights potential advantages balancing multiple evaluation metrics. However, study's limitations suggest future directions, including improvements, expanded metrics, use more diverse conclusions emphasize theoretical practical significance health support systems, indicating wide-ranging applications models.

Language: Английский

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Generative AI in Network Security and Intrusion Detection

Advances in information security, privacy, and ethics book series, Journal Year: 2024, Volume and Issue: unknown, P. 77 - 124

Published: July 26, 2024

Protecting virtual assets from cyber threats is essential as we live in a digitally advanced world. Providing responsible emphasis on proper network security and intrusion detection imperative. On the other hand, traditional strategies need supportive tool to adapt transforming threat space. New generative AI techniques like adversarial networks (GANs) variational autoencoders (VAEs) are mainstream technologies required meet gap. This chapter deals with how these models can enhance by inspecting traffic for anomalies malicious behaviors detected through unsupervised learning, which considers strange or emerging phenomena. survey features innovations fault detection, behavior control, deep packet inspection, classification, examples of real-world intrusions GAN-based systems. Furthermore, focuses challenges attacks that require development solid defense mechanisms, such networks. Ethics becomes following matter our list discussions, given privacy transparency accountability be observed when working security. Finally, authors examine trends determine cyber-attacks dealt comprehensively.

Language: Английский

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Mental illness detection through harvesting social media: a comprehensive literature review

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e2296 - e2296

Published: Oct. 7, 2024

Mental illness is a common disease that at its extremes leads to personal and societal suffering. A complicated multi-factorial disease, mental influenced by number of socioeconomic clinical factors, including individual risk factors. Traditionally, approaches relying on interviews filling out questionnaires have been employed diagnose illness; however, these manual procedures found be frequently prone errors unable reliably identify individuals with illness. Fortunately, people illnesses express their ailments social media, making it possible more precisely harvesting media posts. This study offers thorough analysis how (more specifically, depression) from users’ data. Along the explanation data acquisition, preprocessing, feature extraction, classification techniques, most recent published literature presented give readers understanding subject. Since, in past, majority relevant scientific community has focused using machine learning (ML) deep (DL) models illness, so review also focuses techniques along detail, critical presented. More than 100 DL, ML, natural language processing (NLP) based developed for past reviewed, technical contributions strengths are discussed. There exist multiple studies, discussing extensive complete road map design detection system ML DL methods limited. The includes detail dataset may acquired platforms, preprocessed, features extracted employ detection. Hence, we anticipate this will help learn them comprehensive identifying

Language: Английский

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Clinical, legal and ethical implications of coercion and compulsory treatment in eating disorders: do rapid review findings identify clear answers or more muddy waters?

Journal of Eating Disorders, Journal Year: 2024, Volume and Issue: 12(1)

Published: Oct. 18, 2024

This Rapid Review (RR) aimed to assess the current literature over past decade determine prevailing evidence regarding compulsory treatment* in eating disorders (ED). It is hoped that review will help inform a consensus opinion as whether this course of action confers significant clinical benefit, and importantly, whom it should apply. The also explores alternative options involuntary care. Four indexing databases (OVID; ProQuest; Web Science; PubMed/MedLine) were searched using variations following keywords: "coercive/detained/involuntary/least restrictive care" "treatment refusal" "incarcerated/forced/compulsory admission" "moral/ethic/legal/mental health act" "eating disorder". Research was restricted articles published between 2013 2023 included grey literature. Of 9911 retrieved, 34 for final analyses, exploring ethical, legal, physical mental outcomes treatment. Studies comprised papers, cohort studies, cross sectional research, case series reports, ethnography, commentary papers majority studies focused on individuals with anorexia nervosa (AN). Only two considered treatment other (EDs) Findings largely align previous reviews suggesting saves lives but comes at therapeutic personal cost. remains unknown who may benefit from decision invoke clinician responsibility likely be faced by most their care EDs. Significant gaps remain clear road map clinician-informed submission person ED does not yet exist. Further, there little There efforts concentrated reducing instances minimising coercion through development open, transparent trusting relationships treating clinician. Co-produced research guidelines guided voices lived experience are needed ensure minimisation potential harm. Eating complex psychological numerous consequences associated lethality including heart attack, irregular heartbeat, dehydration, blood clots, risk suicide. Without indicated intervention deterioration acute stages illness, best develop chronic worst lose life. Despite this, frequently refuse medical due fear weight gain, interruption behaviours experienced protective effects experiences Many report sense hopelessness unsuccessful times harmful treatments. presents clinicians practical ethical conundrum: delivered an individual against will? Researchers, policymakers, law professionals alike challenged legal bounds around which practitioners can act beneficence when considering disorder. A commissioned Victorian Government Department Health summarise extant disorders. * Involuntary treatment' 'compulsory synonymous, we have chosen term understood general public/informed readers.

Language: Английский

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