Artificial Intelligence in Mental Health Care: Management Implications, Ethical Challenges, and Policy Considerations DOI Creative Commons

Stephan Hoose,

Kristína Králiková

Administrative Sciences, Год журнала: 2024, Номер 14(9), С. 227 - 227

Опубликована: Сен. 17, 2024

Adopting AI (Artificial Intelligence) in the provision of psychiatric services has been groundbreaking and presented other means handling some issues related to traditional methods. This paper aims at analyzing applicability efficiency mental health practices based on business administration paradigms with a focus managing policies. engages systematic synoptic process, where current technologies are investigated reference literature as their usefulness delivering moral considerations that surround application. The study indicates is capable improving availability, relevance, effectiveness services, information can be useful for policymakers management care. Consequently, specific concerns arise, such how algorithm imposes its own bias, question data privacy, or mechanism could reduce human factor review brought light an area understanding AI-driven interventions not explored: effect long run. field suggests further research should conducted regarding ethical factors, increasing standards usage administration, exploring cooperation practitioners engineers respect application practice. Proposed solutions, therefore, include enhancing functions guaranteeing policy instruments favorable use health.

Язык: Английский

AI-Powered Breakthroughs DOI
Muhammad Usman Tariq

Advances in psychology, mental health, and behavioral studies (APMHBS) book series, Год журнала: 2025, Номер unknown, С. 65 - 92

Опубликована: Янв. 3, 2025

This chapter examines how artificial intelligence (AI) is improving neuropsychological practice and AI tools can be used to diagnose treat rehabilitate cognitive disorders. Through a critical analysis of recent research developing patterns the emphasizes AIs potential for neuropsychology real-time interventions personalized care early detection. It explores has advanced create like virtual assistants chatbots machine learning algorithms that have greatly enhanced testing treatment. in neurorehabilitation shows encouraging results precision effectiveness treatment regimens particularly patients with brain injuries or decline. The also effects on training education focus preparing next generation neuropsychologists settings by AI.

Язык: Английский

Процитировано

6
AI-Powered Innovations Transforming Adaptive Education for Disability Support DOI

Munikrishnaiah Sundara Ramaiah,

Sevinthi Kali Sankar Nagarajan, Pawan Whig

и другие.

Advances in educational technologies and instructional design book series, Год журнала: 2024, Номер unknown, С. 73 - 100

Опубликована: Дек. 30, 2024

This chapter examines artificial intelligence's (AI) transformative impact on adaptive education for students with disabilities. explores how AI-driven technologies, including intelligent tutoring systems, speech recognition tools, and personalized learning algorithms, are reshaping educational experiences to be more inclusive effective. By leveraging these innovations, educators can tailor content support meet individual needs, enhance accessibility, overcome barriers education. Drawing case studies practical examples, the highlights ability of AI revolutionize traditional models by delivering customized, responsive diverse Emphasizing potential foster equity inclusion, underscores its role in advancing opportunities all learners creating a accessible landscape.

Язык: Английский

Процитировано

13
Physical activity and neuroplasticity in neurodegenerative disorders: a comprehensive review of exercise interventions, cognitive training, and AI applications DOI Creative Commons

Lamia Ben Ezzdine,

Wissem Dhahbi, Ismail Dergaa

и другие.

Frontiers in Neuroscience, Год журнала: 2025, Номер 19

Опубликована: Фев. 28, 2025

This review aimed to elucidate the mechanisms through which (i) physical activity (PA) enhances neuroplasticity and cognitive function in neurodegenerative disorders, (ii) identify specific PA interventions for improving rehabilitation programs. We conducted a literature search PubMed, Medline, Scopus, Web of Science, PsycINFO, covering publications from January 1990 August 2024. The strategy employed key terms related neuroplasticity, exercise, function, personalized activity. Inclusion criteria included original research on relationship between while exclusion eliminated studies focusing solely pharmacological interventions. identified multiple pathways may enhance including releasing neurotrophic factors, modulation neuroinflammation, reduction oxidative stress, enhancement synaptic connectivity neurogenesis. Aerobic exercise was found increase hippocampal volume by 1–2% improve executive scores 5–10% older adults. Resistance training enhanced control memory performance 12–18% elderly individuals. Mind–body exercises, such as yoga tai-chi, improved gray matter density memory-related brain regions 3–5% emotional regulation 15–20%. Dual-task attention processing speed 8–14% individuals with disorders. also discuss potential role AI-based AI preventing rehabilitating illnesses, highlighting innovative approaches patient outcomes. significantly disorders various mechanisms. resistance training, mind–body practices, dual-task exercises each offer unique benefits. Implementing these activities clinical settings can Future should focus creating tailored conditions, incorporating programs optimize rehabilitation.

Язык: Английский

Процитировано

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

Sepehr Mojdehdehbaher

AI, Год журнала: 2025, Номер 6(3), С. 62 - 62

Опубликована: Март 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.

Язык: Английский

Процитировано

1
Assessing and recovering Alzheimer’s disease: a comparative analysis of standard neuropsychological approaches and virtual reality interventions with the use of digital storytelling DOI Creative Commons
Fabrizio Stasolla,

Mariacarla Di Gioia,

Irene Messina

и другие.

Frontiers in Psychology, Год журнала: 2024, Номер 15

Опубликована: Июль 24, 2024

Background Alzheimer’s disease (AD), the most common form of dementia, is a progressive neurodegenerative disorder that predominantly affects elderly population. Traditional assessment methods, including neuropsychological tests like MMSE, have been cornerstone AD diagnosis for decades. These methods are grounded in wealth research and clinical experience, providing robust framework understanding cognitive deficits AD. The evolution rehabilitation has recently tackled with introduction Virtual Reality (VR) technologies. Objectives To evaluate use storytelling reminiscence therapy virtual reality programs as complementary enhancing modality alongside standard patients. explore how regular interaction VR narratives can slow decline or improve relevant features functioning over time. propose new rehabilitative tool based on digital storytelling. Method A comparative analysis Standard Neuropsychological Approaches Interventions patients Alzheimer was carried out. literature overview empirical studies between 2019 2024 conducted. Results We VR-based setup mediated by recovery Conclusion employment within positively impact both emotional realms patients, beneficial outcomes caregivers’ families’ burden. successful implementation this approach requires careful consideration accessibility, data interpretation, validation protocols.

Язык: Английский

Процитировано

5
Integration of rehabilitation and palliative care in cancer management: A futuristic model DOI
Raktim Swarnakar,

Shiv Lal Yadav

World Journal of Clinical Cases, Год журнала: 2025, Номер 13(12)

Опубликована: Янв. 7, 2025

It explores the integration of rehabilitation and palliative care in cancer management, advocating for a holistic approach that addresses diverse needs patients throughout their treatment journey. Traditional often prioritizes curative interventions at expense overall well-being, leading to fragmented experience patients. By combining rehabilitation-focused on restoring function improving physical health-with care-emphasizing symptom management quality life-healthcare providers can create comprehensive support system. The essay highlights importance interdisciplinary collaboration among healthcare professionals, as well need education training implement this integrated model effectively. Additionally, it potential barriers such funding limitations institutional resistance. Ultimately, these two disciplines represents critical evolution care, enhancing patient outcomes ensuring individuals receive compassionate, patient-centered

Язык: Английский

Процитировано

0
Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem DOI

Michael J. Ormond,

Eric H Garling,

J. Woo

и другие.

Arthroscopy The Journal of Arthroscopic and Related Surgery, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Deep Learning and Reinforcement Learning for Assessing and Enhancing Academic Performance in University Students: A Scoping Review DOI Creative Commons
Fabrizio Stasolla, Antonio Zullo,

Roberto Maniglio

и другие.

AI, Год журнала: 2025, Номер 6(2), С. 40 - 40

Опубликована: Фев. 19, 2025

University students often face challenges in managing academic demands and difficulties like time management, task prioritization, effective study strategies. This scoping review investigates the application of Deep Learning (DL) Reinforcement (RL) evaluating enhancing performance, focusing on their practical applications, limitations, future potential. Using PRISMA guidelines, 27 empirical studies published between 2014 2024 were analyzed. These utilized advanced DL RL technologies, including neural networks adaptive algorithms, to support personalized learning performance prediction across diverse university contexts. Key findings highlight DL’s ability accurately predict outcomes identify at-risk students, with models achieving high accuracy areas dropout language proficiency assessments. proved optimizing pathways tailoring interventions, dynamically adapting individual student needs. The emphasizes significant improvements grades, engagement, efficiency enabled by AI-driven systems. However, persist, scalability, resource demands, need for transparent interpretable models. Future research could focus datasets, multimodal inputs, long-term evaluations enhance applicability these technologies. By integrating RL, higher education can foster personalized, environments, improving inclusivity.

Язык: Английский

Процитировано

0
Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery DOI
Spandana Rajendra Kopalli, Madhu Shukla,

B Jayaprakash

и другие.

Neuroscience, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Hybrid AI‐Driven Bio‐Inspired Wearable Sensors With Aquasense AI Technology for Multimodal Health Monitoring and Rehabilitation in Dynamic Environments DOI Open Access

J. Poongodi,

K Kavitha,

S. Sathish

и другие.

Transactions on Emerging Telecommunications Technologies, Год журнала: 2025, Номер 36(3)

Опубликована: Фев. 28, 2025

ABSTRACT AquaSense AI is a bio‐inspired, wearable sensor system that enables paradigmatic shift in healthcare and physiotherapy, emulating nature's sensory capabilities of aquatic animals. Flexible, waterproof sensors are used to detect human motion, balance, posture on land water. perfect for application swimming pools hydrotherapy sessions. delivers real‐time, high‐precision feedback enable effective rehabilitation, fall prevention, fitness monitoring. In Under water, these follow person's the coordination their limbs through detection pressure changes, while land, they monitor gait, posture, balance. The sophisticated algorithms within system, including Hierarchical Adaptive Neural Network (HANN) Multimodal Self‐Learning Framework, adjust sensitivity environment provide personalized over time, continuously adapting movements rehabilitation progress user. bio‐inspired design, adaptive AI, real‐time predictive analytics can dual functionality at clinical applications, improving safety, outcomes, general health monitoring diverse environments.

Язык: Английский

Процитировано

0