An Overview of Tools and Technologies for Anxiety and Depression Management Using AI DOI Open Access

Adrianos Pavlopoulos,

Theodoros Rachiotis, Ilias Maglogiannis

et al.

Published: Aug. 13, 2024

This study aims to evaluate the utilization and effectiveness of artificial intelligence (AI) applications in managing symptoms anxiety depression. The primary objectives are identify current AI tools, analyze their practicality efficacy, assess potential benefits risks. A comprehensive literature review was conducted using databases such as ScienceDirect, Google Scholar, PubMed, ResearchGate, focusing on publications from last five years. search utilized keywords including "artificial intelligence," "applications," "mental health," "anxiety," "LLMs" "depression". Various chatbots, mobile applications, wearables, virtual reality settings, large language models (LLMs), were examined categorized based functions mental health care. findings indicate that LLMs, show significant promise symptom management, offering accessible personalized interventions can complement traditional treatments. Tools AI-driven apps, LLMs have demonstrated efficacy reducing depression, improving user engagement outcomes. particular, shown enhancing therapeutic diagnostic treatment plans by providing immediate support resources, thus workload professionals. However, limitations include concerns over data privacy, for over-reliance technology, need human oversight ensure Ethical considerations, security balance between interaction, also addressed. concludes while AI, has significantly aid care, it should be used a to, rather than replacement for, therapists. Future research focus measures, integrating tools with methods, exploring long-term effects health. Further investigation is needed across diverse populations settings.

Language: Английский

Ethical challenges and opportunities in applying artificial intelligence to cardiovascular medicine DOI Creative Commons

Stephen Lewin,

Riti Chetty,

Abdul Rahman Ihdayhid

et al.

Canadian Journal of Cardiology, Journal Year: 2024, Volume and Issue: 40(10), P. 1897 - 1906

Published: July 20, 2024

Much anticipation surrounds artificial intelligence's (AI) emergence as a promising tool in health care. It offers potential to revolutionise clinical practice through assistive and autonomous operation. The high prevalence of cardiac disease globally provides an opportunity for AI technology increase care efficiency improve patient outcomes. This article explores the ethical considerations necessary safe acceptable implantation within space. We aim highlight several challenges such data privacy, consent, sustainability, cybersecurity. In addition, we outline future opportunities use cardiovascular medicine. Overall, argue that deployment demands robust regulation, transparent algorithms, safeguarding privacy.

Language: Английский

Citations

10
Digital biomarkers: 3PM approach revolutionizing chronic disease management — EPMA 2024 position DOI Creative Commons
Ivica Smokovski,

Nanette Steinle,

Andrew Behnke

et al.

The EPMA Journal, Journal Year: 2024, Volume and Issue: 15(2), P. 149 - 162

Published: May 11, 2024

Abstract Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels emerged as valuable tools to manage NCDs. DBs refer measurable quantifiable physiological, behavioral, environmental parameters collected for an individual through innovative technologies, including wearables, smart devices, medical sensors. By leveraging healthcare providers can gather real-time data insights, enabling them deliver more proactive tailored interventions individuals at risk patients diagnosed with Continuous monitoring relevant wearable devices or smartphone applications allows clinicians track progression NCDs in real time. With introduction (DBM), new quality primary secondary is being offered promising opportunities assessment protection against health-to-disease transitions vulnerable sub-populations. DBM enables take most cost-effective targeted preventive measures, detect disease developments early, introduce personalized interventions. Consequently, they benefit life (QoL) affected individuals, economy, society large. instrumental paradigm shift from reactive services 3PM approach promoted by European Association Predictive, Preventive, Personalized Medicine (EPMA) involving experts 55 countries This position manuscript consolidates multi-professional expertise area, demonstrating clinically examples providing roadmap implementing concepts facilitated DBs.

Language: Английский

Citations

9
Biomarkers, Omics and Artificial Intelligence for Early Detection of Pancreatic Cancer. DOI Creative Commons
Kate Murray, Lucy Oldfield, Irena Stefanova

et al.

Seminars in Cancer Biology, Journal Year: 2025, Volume and Issue: 111, P. 76 - 88

Published: Feb. 20, 2025

Language: Английский

Citations

1
Beyond Limits: The Fusion of Nature and Technology in Achieving Optimal Health—The Truth of Biohacking DOI

Dorothea Portius

Published: Jan. 1, 2025

Language: Английский

Citations

1
AI-Driven Telerehabilitation: Benefits and Challenges of a Transformative Healthcare Approach DOI Creative Commons
Rocco Salvatore Calabrò,

Sepehr Mojdehdehbaher

AI, Journal Year: 2025, Volume and Issue: 6(3), P. 62 - 62

Published: March 17, 2025

Artificial intelligence (AI) has revolutionized telerehabilitation by integrating machine learning (ML), big data analytics, and real-time feedback to create adaptive, patient-centered care. AI-driven systems enhance analyzing patient personalize therapy, monitor progress, suggest adjustments, eliminating the need for constant clinician oversight. The benefits of AI-powered include increased accessibility, especially remote or mobility-limited patients, greater convenience, allowing patients perform therapies at home. However, challenges persist, such as privacy risks, digital divide, algorithmic bias. Robust encryption protocols, equitable access technology, diverse training datasets are critical addressing these issues. Ethical considerations also arise, emphasizing human oversight maintaining therapeutic relationship. AI aids clinicians automating administrative tasks facilitating interdisciplinary collaboration. Innovations like 5G networks, Internet Medical Things (IoMT), robotics further telerehabilitation’s potential. By transforming rehabilitation into a dynamic, engaging, personalized process, together represent paradigm shift in healthcare, promising improved outcomes broader worldwide.

Language: Английский

Citations

1
Artificial Intelligence in Atrial Fibrillation: From Early Detection to Precision Therapy DOI Open Access
Paschalis Karakasis, Panagiotis Theofilis, Μarios Sagris

et al.

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(8), P. 2627 - 2627

Published: April 11, 2025

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, associated with significant morbidity, mortality, and healthcare burden. Despite advances in AF management, challenges persist early detection, risk stratification, treatment optimization, necessitating innovative solutions. Artificial intelligence (AI) has emerged as a transformative tool care, leveraging machine learning deep algorithms to enhance diagnostic accuracy, improve prediction, guide therapeutic interventions. AI-powered electrocardiographic screening demonstrated ability detect asymptomatic AF, while wearable photoplethysmography-based technologies have expanded real-time rhythm monitoring beyond clinical settings. AI-driven predictive models integrate electronic health records multimodal physiological data refine stroke anticoagulation decision making. In realm of treatment, AI revolutionizing individualized therapy optimizing management catheter ablation strategies. Notably, AI-enhanced electroanatomic mapping procedural guidance hold promise for improving success rates reducing recurrence. these advancements, integration remains an evolving field. Future research should focus on large-scale validation, model interpretability, regulatory frameworks ensure widespread adoption. This review explores current emerging applications highlighting its potential precision medicine patient outcomes.

Language: Английский

Citations

1
Advancing nursing education through wearable electronic devices: A scoping review DOI Creative Commons
Agostinho Antônio Cruz Araújo, Lucas Gardim, Jordana Salma

et al.

Nurse Education in Practice, Journal Year: 2024, Volume and Issue: 79, P. 104032 - 104032

Published: June 25, 2024

Language: Английский

Citations

7
Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients DOI Open Access
Weronika Magdalena Żydowicz, Jarosław Skokowski, Luigi Marano

et al.

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(15), P. 4337 - 4337

Published: July 25, 2024

BC, affecting both women and men, is a complex disease where early diagnosis plays crucial role in successful treatment enhances patient survival rates. The Metaverse, virtual world, may offer new, personalized approaches to diagnosing treating BC. Although Artificial Intelligence (AI) still its stages, rapid advancement indicates potential applications within the healthcare sector, including consolidating information one accessible location. This could provide physicians with more comprehensive insights into details. Leveraging Metaverse facilitate clinical data analysis improve precision of diagnosis, potentially allowing for tailored treatments BC patients. However, while this article highlights possible transformative impacts technologies on treatment, it important approach these developments cautious optimism, recognizing need further research validation ensure enhanced care greater accuracy efficiency.

Language: Английский

Citations

7
Investigating superior performance by configuring bimetallic electrodes on fabric triboelectric nanogenerators (F-TENGs) for IoT enabled touch sensor applications DOI Creative Commons

Akshaya Kumar Aliyana,

Satyaranjan Bairagi, Charchit Kumar

et al.

Nano Energy, Journal Year: 2024, Volume and Issue: 130, P. 110125 - 110125

Published: Aug. 15, 2024

Fabric Triboelectric Nanogenerators (F-TENGs) are increasingly becoming more significant in wearable monitoring and beyond.These devices offer autonomous energy generation sensing capabilities, by replacing conventional batteries flexible wearables.Despite the substantial effort, however, achieving high output with optimal stability, durability, comfort, washability poses challenges, so we have yet to see any practical commercial uses of these materials.This study focuses on investigates impacts mono bimetallic composite fabric electrode configurations performance F-TENGs.Our findings showcase superiority configurations, particularly those incorporating Copper (Cu) Nickel (Ni), over monometallic (Cu only) electrodes.These demonstrate remarkable results, exhibiting a maximum instantaneous voltage, current, power density ~199 V (a twofold increase compared configurations), ~22 μA threefold 2992 mW/m 2 , respectively.Notably, also exhibit exceptional flexibility, shape adaptability, structural integrity, washability, mechanical stability.Furthermore, integration passive component-based management circuits significantly enhances capabilities F-TENGs, highlighting essential role selection optimizing F-TENGs.In addition, developed complete IoT-enabled touch sensor system using CuNi-BEF EcoFlex layered F-TENGs for precise detection soft hard touches.This advanced robotic functionality, enabling nuanced understanding precision tasks fostering intuitive human-machine interactions.

Language: Английский

Citations

7
An Overview of Tools and Challenges for Safety Evaluation and Exposure Assessment in Industry 4.0 DOI Creative Commons
Spyridon Damilos, Stratos Saliakas,

Dimitris Karasavvas

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(10), P. 4207 - 4207

Published: May 15, 2024

Airborne pollutants pose a significant threat in the occupational workplace resulting adverse health effects. Within Industry 4.0 environment, new systems and technologies have been investigated for risk management as safety smart tools. The use of predictive algorithms via artificial intelligence (AI) machine learning (ML) tools, real-time data exchange Internet Things (IoT), cloud computing, digital twin (DT) simulation provide innovative solutions accident prevention mitigation. Additionally, sensors, wearable devices virtual (VR) augmented reality (AR) platforms can support training employees practices signal alarming concentrations airborne hazards, providing designing strategies hazard control options. Current reviews outline drawbacks challenges these technologies, including elevated stress levels employees, cyber-security, handling, privacy concerns, while highlighting limitations. Future research should focus on ethics, policies, regulatory aspects technologies. This perspective puts together advances innovations terms exposure assessment, aiding understanding full potential supporting their application industrial manufacturing environments.

Language: Английский

Citations

6