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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Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives

International Journal of Educational Technology in Higher Education, Journal Year: 2024, Volume and Issue: 21(1)

Published: March 25, 2024

Abstract In recent years, higher education (HE) globally has witnessed extensive adoption of technology, particularly in teaching and research. The emergence generative Artificial Intelligence (GenAI) further accelerates this trend. However, the increasing sophistication GenAI tools raised concerns about their potential to automate research processes. Despite widespread on various fields, there is a lack multicultural perspectives its impact HE. This study addresses gap by examining usage, benefits, from standpoint. We employed an online survey that collected responses 1217 participants across 76 countries, encompassing broad range gender categories, academic disciplines, geographical locations, cultural orientations. Our findings revealed high level awareness familiarity with among respondents. A significant portion had prior experience expressed intention continue using these tools, primarily for information retrieval text paraphrasing. emphasizes importance integration education, highlighting both benefits concerns. Notably, strong correlation between dimensions respondents’ views related GenAI, including as dishonesty need ethical guidelines. We, therefore, argued responsible use can enhance learning processes, but addressing may require robust policies are responsive expectations. discussed offered recommendations researchers, educators, policymakers, aiming promote effective education.

Language: Английский

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Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time

Sensors, Journal Year: 2023, Volume and Issue: 23(11), P. 5204 - 5204

Published: May 30, 2023

With an aging population and increased chronic diseases, remote health monitoring has become critical to improving patient care reducing healthcare costs. The Internet of Things (IoT) recently drawn much interest as a potential remedy. IoT-based systems can gather analyze wide range physiological data, including blood oxygen levels, heart rates, body temperatures, ECG signals, then provide real-time feedback medical professionals so they may take appropriate action. This paper proposes system for early detection problems in home clinical settings. comprises three sensor types: MAX30100 measuring level rate; AD8232 module signal data; MLX90614 non-contact infrared temperature. collected data is transmitted server using the MQTT protocol. A pre-trained deep learning model based on convolutional neural network with attention layer used classify diseases. detect five different categories heartbeats: Normal Beat, Supraventricular premature beat, Premature ventricular contraction, Fusion ventricular, Unclassifiable beat from fever or non-fever Furthermore, provides report patient's rate level, indicating whether are within normal ranges not. automatically connects user nearest doctor further diagnosis if any abnormalities detected.

Language: Английский

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The effects of artificial intelligence applications in educational settings: Challenges and strategies

Technological Forecasting and Social Change, Journal Year: 2023, Volume and Issue: 199, P. 123076 - 123076

Published: Dec. 14, 2023

With the continuous intervention of AI tools in education sector, new research is required to evaluate viability and feasibility extant platforms inform various pedagogical methods instruction. The current manuscript explores cumulative published literature date order key challenges that influence implications adopting models Education Sector. researchers' present works both favour against AI-based applications within Academic milieu. A total 69 articles from a 618-article population was selected diverse academic journals between 2018 2023. After careful review articles, presents classification structure based on five distinct dimensions: user, operational, environmental, technological, ethical challenges. recommends use ChatGPT as complementary teaching-learning aid including need afford customized optimized versions tool for teaching fraternity. study addresses an important knowledge gap how enhance educational settings. For instance, discusses interalia range AI-related effects learning creative prompts, training datasets genres, incorporation human input data confidentiality elimination bias. concludes by recommending strategic solutions emerging identified while summarizing ways encourage wider adoption other sector. insights presented this can act reference policymakers, teachers, technology experts stakeholders, facilitate means sector more generally. Moreover, provides foundation future research.

Language: Английский

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Artificial intelligence in the field of pharmacy practice: A literature review

Exploratory Research in Clinical and Social Pharmacy, Journal Year: 2023, Volume and Issue: 12, P. 100346 - 100346

Published: Oct. 21, 2023

Artificial intelligence (AI) is a transformative technology used in various industrial sectors including healthcare. In pharmacy practice, AI has the potential to significantly improve medication management and patient care. This review explores applications field of practice. The incorporation technologies provides pharmacists with tools systems that help them make accurate evidence-based clinical decisions. By using algorithms Machine Learning, can analyze large volume data, medical records, laboratory results, profiles, aiding identifying drug-drug interactions, assessing safety efficacy medicines, making informed recommendations tailored individual requirements. Various models have been developed predict detect adverse drug events, assist decision support medication-related decisions, automate dispensing processes community pharmacies, optimize dosages, adherence through smart technologies, prevent errors, provide therapy services, telemedicine initiatives. incorporating into health care professionals augment their decision-making patients personalized allows for greater collaboration between different healthcare services provided single patient. For patients, may be useful tool providing guidance on how when take medication, education, promoting know where obtain most cost-effective best communicate professionals, monitoring wearables devices, everyday lifestyle guidance, integrate diet exercise.

Language: Английский

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Ethical Implications of Chatbot Utilization in Nephrology

Journal of Personalized Medicine, Journal Year: 2023, Volume and Issue: 13(9), P. 1363 - 1363

Published: Sept. 8, 2023

This comprehensive critical review critically examines the ethical implications associated with integrating chatbots into nephrology, aiming to identify concerns, propose policies, and offer potential solutions. Acknowledging transformative of in healthcare, responsible implementation guided by considerations is utmost importance. The underscores significance establishing robust guidelines for data collection, storage, sharing safeguard privacy ensure security. Future research should prioritize defining appropriate levels access, exploring anonymization techniques, implementing encryption methods. Transparent usage practices obtaining informed consent are fundamental considerations. Effective security measures, including technologies secure transmission protocols, indispensable maintaining confidentiality integrity patient data. To address biases discrimination, suggests regular algorithm reviews, diversity strategies, ongoing monitoring. Enhancing clarity chatbot capabilities, developing user-friendly interfaces, explicit procedures essential consent. Striking a balance between automation human intervention vital preserve doctor-patient relationship. Cultural sensitivity multilingual support be considered through training. utilization it imperative development frameworks encompassing handling, security, bias mitigation, consent, collaboration. Continuous innovation this field crucial maximizing technology ultimately improving outcomes.

Language: Английский

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Analyzing the impact of artificial intelligence on employee productivity: the mediating effect of knowledge sharing and well‐being

Asia Pacific Journal of Human Resources, Journal Year: 2023, Volume and Issue: 61(4), P. 794 - 820

Published: June 29, 2023

Following social cognitive theory, the current study investigated impact of artificial intelligence (AI) on employees' productivity in healthcare sector. AI significantly facilitates management hospitals to vigilantly assess employees’ and accurately analyze characteristics, such as attitude, emotion behavior. With underlying mechanism employee mental health well‐being, knowledge sharing, has considered beneficial harmful perspectives workplace. The also hypothesizes important moderating role technological leadership. data was collected from 184 doctors Pakistan's major hospitals. Partial least squares (PLS) results support a direct relationship between productivity. findings supported sharing well‐being However, leadership effect found be insignificant. It opens an avenue for this further research future directions.

Language: Английский

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Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public

Family Medicine and Community Health, Journal Year: 2024, Volume and Issue: 12(Suppl 1), P. e002583 - e002583

Published: Jan. 1, 2024

Background Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI’s role in evaluating prognosis and long-term outcomes depressive disorders, offering insights into how AI large language models (LLMs) compare with human perspectives. Methods Using case vignettes, we conducted a comparative analysis involving different LLMs (ChatGPT-3.5, ChatGPT-4, Claude Bard), professionals (general practitioners, psychiatrists, clinical psychologists nurses), general public that reported previously. We evaluate ability generate prognosis, anticipated without professional intervention, envisioned positive negative consequences for individuals depression. Results In most examined cases, four consistently identified depression as primary diagnosis recommended combined treatment psychotherapy antidepressant medication. ChatGPT-3.5 exhibited significantly pessimistic distinct from other LLMs, public. Bard aligned closely perspectives, all whom no improvement or worsening help. Regarding outcomes, ChatGPT 3.5, projected fewer than ChatGPT-4. Conclusions underscores complement expertise promote collaborative paradigm healthcare. The observation three mirrored anticipations experts scenarios technology’s prospective value forecasts. outlook presented by 3.5 is concerning, it could potentially diminish patients’ drive initiate continue therapy. summary, although show enhancing healthcare services, their utilisation requires thorough verification seamless integration judgement skills.

Language: Английский

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Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach

International Journal of Information Management, Journal Year: 2024, Volume and Issue: 77, P. 102781 - 102781

Published: April 3, 2024

Artificial intelligence (AI) is playing a leading role in the digital transformation of enterprises, particularly manufacturing industry where it has been responsible for profound key business and production operations. Despite accelerated growth AI technologies, knowledge implementation by small medium-sized enterprises (SMEs) remains underexplored. Thus, this study seeks to examine how SMEs orchestrate resources implementation. Building on resource orchestration (RO) theory recent work implementation, we investigate multiple case studies involving Sweden operating packaging, plastic, metal sectors. Our findings indicate that structure portfolio based acquiring accumulating resources. are bundled into learning governance capabilities leverage configurations Through dynamic process orchestration, effectively mobilising coordinating processes, empowering skilled people. This research contributes existing practice academic literature highlighting drive an organisation's whilst creating competitive advantage.

Language: Английский

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Artificial intelligence in healthcare delivery: Prospects and pitfalls

Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100108 - 100108

Published: April 16, 2024

This review provides a comprehensive examination of the integration Artificial Intelligence (AI) into healthcare, focusing on its transformative implications and challenges. Utilising systematic search strategy across electronic databases such as PubMed, Scopus, Embase, Sciencedirect, relevant peer-reviewed articles published in English between January 2010 till date were identified. Findings reveal AI's significant impact healthcare delivery, including role enhancing diagnostic precision, enabling treatment personalisation, facilitating predictive analytics, automating tasks, driving robotics. AI algorithms demonstrate high accuracy analysing medical images for disease diagnosis enable creation tailored plans based patient data analysis. Predictive analytics identify high-risk patients proactive interventions, while AI-powered tools streamline workflows, improving efficiency experience. Additionally, AI-driven robotics automate tasks enhance care particularly rehabilitation surgery. However, challenges quality, interpretability, bias, regulatory frameworks must be addressed responsible implementation. Recommendations emphasise need robust ethical legal frameworks, human-AI collaboration, safety validation, education, regulation to ensure effective healthcare. valuable insights potential advocating implementation efficacy.

Language: Английский

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