Enhancing mental health with Artificial Intelligence: Current trends and future prospects

Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100099 - 100099

Published: April 17, 2024

Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application mental healthcare is no exception. Hence, this review explores the integration of AI into healthcare, elucidating current trends, ethical considerations, future directions dynamic field. This encompassed recent studies, examples applications, considerations shaping Additionally, regulatory frameworks trends research development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, Google Scholar). The inclusion criteria papers published peer-reviewed journals, conference proceedings, or reputable online databases, that specifically focus on field offer comprehensive overview, analysis, existing literature English language. Current reveal AI's potential, with applications such early detection health disorders, personalized treatment plans, AI-driven virtual therapists. However, these advancements are accompanied by challenges concerning privacy, bias mitigation, preservation human element therapy. Future emphasize need for clear frameworks, transparent validation models, continuous efforts. Integrating therapy represents promising frontier healthcare. While holds potential to revolutionize responsible implementation essential. By addressing thoughtfully, we may effectively utilize enhance accessibility, efficacy, ethicality thereby helping both individuals communities.

Language: Английский

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Recent Progress in Micro- and Nanotechnology-Enabled Sensors for Biomedical and Environmental Challenges

Sensors, Journal Year: 2023, Volume and Issue: 23(12), P. 5406 - 5406

Published: June 7, 2023

Micro- and nanotechnology-enabled sensors have made remarkable advancements in the fields of biomedicine environment, enabling sensitive selective detection quantification diverse analytes. In biomedicine, these facilitated disease diagnosis, drug discovery, point-of-care devices. environmental monitoring, they played a crucial role assessing air, water, soil quality, as well ensured food safety. Despite notable progress, numerous challenges persist. This review article addresses recent developments micro- for biomedical challenges, focusing on enhancing basic sensing techniques through micro/nanotechnology. Additionally, it explores applications addressing current both domains. The concludes by emphasizing need further research to expand capabilities sensors/devices, enhance sensitivity selectivity, integrate wireless communication energy-harvesting technologies, optimize sample preparation, material selection, automated components sensor design, fabrication, characterization.

Language: Английский

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Wearable Devices: Implications for Precision Medicine and the Future of Health Care

Annual Review of Medicine, Journal Year: 2023, Volume and Issue: 75(1), P. 401 - 415

Published: Nov. 20, 2023

Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive continuous monitoring vital physiological parameters. Recent advances in disciplines including electronics, computation, material science have resulted affordable highly wearable that routinely used for tracking managing health well-being. Combined longitudinal parameters, wearables poised to transform the early detection, diagnosis, treatment/management a range clinical conditions. Smartwatches most commonly already demonstrated valuable biomedical potential detecting conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant promise shown research settings, there remain major hurdles translating medical uses clinic. There is clear need effective collaboration among stakeholders, users, data scientists, clinicians, payers, governments, improve device security, user privacy, standardization, regulatory approval, validity. This review examines offer reliable measures status on par FDA-approved specialized devices. We briefly examine studies where proved critical detection acute chronic particular focus cardiovascular viral infections, mental health. Finally, we discuss current obstacles implementation provide perspectives their deliver increasingly personalized proactive care across wide variety

Language: Английский

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Approaches of wearable and implantable biosensor towards of developing in precision medicine

Frontiers in Medicine, Journal Year: 2024, Volume and Issue: 11

Published: July 18, 2024

In the relentless pursuit of precision medicine, intersection cutting-edge technology and healthcare has given rise to a transformative era. At forefront this revolution stands burgeoning field wearable implantable biosensors, promising paradigm shift in how we monitor, analyze, tailor medical interventions. As these miniature marvels seamlessly integrate with human body, they weave tapestry real-time health data, offering unprecedented insights into individual physiological landscapes. This log embarks on journey realm where convergence biology heralds new dawn personalized healthcare. Here, explore intricate web innovations, challenges, immense potential bioelectronics sentinels hold sculpting future medicine.

Language: Английский

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The Potential of Wearable Sensors for Detecting Cognitive Rumination: A Scoping Review

Sensors, Journal Year: 2025, Volume and Issue: 25(3), P. 654 - 654

Published: Jan. 23, 2025

Cognitive rumination, a transdiagnostic symptom across mental health disorders, has traditionally been assessed through self-report measures. However, these measures are limited by their temporal nature and subjective bias. The rise in wearable technologies offers the potential for continuous, real-time monitoring of physiological indicators associated with rumination. This scoping review investigates current state research on using technology to detect cognitive Specifically, we examine sensors devices used, biomarkers measured, standard rumination comparative validity specific identifying was performed according Preferred Reporting Items Systematic reviews Meta-Analyses (PRISMA) guidelines IEEE, Scopus, PubMed, PsycInfo databases. Studies that used measure rumination-related responses were included (n = 9); seven studies one biomarker, two biomarkers. Electrodermal Activity (EDA) capturing skin conductance activity emerged as both most prevalent sensor 5) comparatively valid biomarker detecting via devices. Other commonly investigated electrical brain measured Electroencephalogram (EEG) 2), Heart Rate Variability (HRV) Electrocardiogram (ECG) heart rate fitness monitors muscle response Electromyography (EMG) 1) movement an accelerometer 1). Empatica E4 Embrace 2 wrist-worn frequently 3). Rumination Response Scale (RRS), widely scale assessing Experimental induction protocols, often adapted from Nolen-Hoeksema Morrow’s 1993 paradigm, also used. In conclusion, findings suggest promise field is still developing, further needed validate explore impact individual traits contextual factors accuracy detection.

Language: Английский

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Modern Smart Gadgets and Wearables for Diagnosis and Management of Stress, Wellness, and Anxiety: A Comprehensive Review

Healthcare, Journal Year: 2025, Volume and Issue: 13(4), P. 411 - 411

Published: Feb. 14, 2025

The increasing development of gadgets to evaluate stress, wellness, and anxiety has garnered significant attention in recent years. These technological advancements aim expedite the identification subsequent treatment these prevalent conditions. This study endeavors critically examine latest smart portable techniques utilized for diagnosing depression, emotional trauma while also exploring underlying biochemical processes associated with their identification. Integrating various detectors within smartphones bands enables continuous monitoring recording user activities. Given widespread use, smartphones, smartwatches, wristbands have become indispensable our daily lives, prompting exploration potential stress detection prevention. When individuals experience nervous system responds by releasing hormones, which can be easily identified quantified bands. this paper focused on examination consistently employed "heart rate variability" (HRV) characteristics diagnostic purposes, superior outcomes observed when HRV was combined "electroencephalogram" (EEG) analysis. Recent research indicates that electrodermal activity (EDA) demonstrates remarkable precision identifying anxiety. Comparisons HRV, EDA, breathing reveal mean heart several commercial wearable products is less accurate stress. comprehensive review article provides an evidence-based evaluation intelligent sensors, highlighting accurately assess It identifies areas further development.

Language: Английский

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Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes

Singapore Medical Journal, Journal Year: 2024, Volume and Issue: 65(3), P. 141 - 149

Published: March 1, 2024

Abstract Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson’s disease essential tremor) is rapidly increasing. Current diagnosis monitoring these rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective time-consuming. To address challenges, utilisation artificial intelligence (AI) has emerged. This review explores advantages challenges associated with using AI-driven video care for elderly patients disorders. The AI-based systems offer improved efficiency objectivity in remote patient monitoring, enabling real-time analysis data, more uniform outcomes augmented support trials. However, such as quality, privacy compliance noisy training labels, during development need be addressed. Ultimately, advancement expected evolve towards discreet, home-based evaluations routine daily activities. progression must incorporate data security, ethical considerations adherence regulatory standards.

Language: Английский

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Developing a supervised learning model for anticipating potential technology convergence between technology topics

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 203, P. 123352 - 123352

Published: April 1, 2024

Language: Английский

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Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Journal of Personalized Medicine, Journal Year: 2023, Volume and Issue: 13(12), P. 1703 - 1703

Published: Dec. 12, 2023

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving technology. However, using machine in poses challenges related availability, such as incomplete, unstructured, fragmented data, well issues privacy, security, format standardization. Furthermore, there is a risk of bias discrimination models. Thus, developing an accurate prediction model from scratch can be expensive complicated task that often requires extensive experiments complex computations. Transfer methods emerged feasible solution address these by transferring knowledge previously trained develop high-performance models for new task. This survey paper provides comprehensive study the effectiveness transfer applications enhance accuracy efficiency diagnoses prognoses, improve healthcare services. The first part this presents discusses most common technologies valuable resources applications, including learning. second meaning learning, clarifying categories types transfer. It also explains strategies, their role addressing models, specifically on data. These include feature extraction, fine-tuning, domain adaptation, multitask federated few-/single-/zero-shot highlights key features each method strategy, limitations applications. Overall, which aims inspire researchers gain approaches health, current strategies overcome limitations, apply them variety technologies.

Language: Английский

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Multimodal Quantitative Research on the Emotional Attachment Characteristics between People and the Built Environment Based on the Immersive VR Eye-Tracking Experiment

Land, Journal Year: 2024, Volume and Issue: 13(1), P. 52 - 52

Published: Jan. 2, 2024

The campus landscape contributes a lot to students’ mental and physical health. Students’ emotional attachment space is an important scientific basis for design. This study used immersive virtual reality eye tracking supported by HTC Vivo Pro scale investigate the relationship between different elements visual behavior attachment. ErgoLab SPSS were analyze indicators. results showed that: (1) Artificial more likely attract attention continuously enhance their interest in landscape. (2) waterscape was attention, while attractiveness of arbors shrubs related color spatial location. (3) characteristics nature generally conducive establishment attachment, including both natural artificial structures that could reflect texture time traces. (4) Three-dimensional sequence design significantly affected focus experience. further contribute providing clearer understanding how preference specific can be obtained decision making planning management during renewal

Language: Английский

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