Sustainable E-Health: Energy-Efficient Tiny AI for Epileptic Seizure Detection via EEG by Moez Hizem, Mohamed Ould-Elhassen Aoueileyine, Samir Brahim Belhaouari, Abdelfatteh EL Omri, Ridha Bouallegue

“…This study aimed to (i) Develop a TinyML workflow that details the steps for model creation and deployment in resource-constrained environments and (ii) apply the workflow to e-health applications for the real-time detection of epileptic seizures using electroencephalography (EEG) data. The methodology employs a dataset of 4097 EEG recordings per patient, each 23.5 seconds long, from 500 patients, to develop a robust and resilient model. …”
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Development of a matching framework for voluntary services provided to home-dwelling older adults by nursing faculty and students based on the Kano model by Lei Huang, Weihong Yang, Lina Wang, Pei Wang, Yan Lin, Shuyao Hui, Peng Wang, Xiang Sun, Yue Yao, Rui Chen, Fengjian Zhang, Lulu Liao, Yilan Liu, Chunyan Guan

“…However, evidence is limited on how to align their needs with the service intentions of nursing faculty and students to develop appropriate frameworks. Methods Data were collected through self-designed demand-supply matching questionnaires from nursing faculty and students (March 26 - April 25, 2023) and older adults (May 24 - July 7, 2023) using convenience sampling. …”
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CHALLENGES FOR INTEGRATION OF REMOTELY PILOTED AIRCRAFT SYSTEMS INTO THE EUROPEAN SKY by Tadeusz ZIELIŃSKI, Wiesław MARUD

“…Despite the undeniable social benefits of RPAS utilisation, in particular in ensuring security and public order, it will be necessary to address issues related to the perception of RPAS by the public, including privacy and data protection, law enforcement associated with the application of RPAS, third-party liability and insurance requirements of RPAS.…”
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Conditions for and potential solutions associated with continuity of care for patients with complex care needs across Swedish regions with differing population densities by Linda Ljungholm, Charlotte Klinga, Mirjam Ekstedt, Anette Edin-Liljegren, Elin-Sofie Forsgärde

“…Method Secondary analysis was conducted using qualitative content analysis on interview data from two studies, consisting of 53 transcripts from individual, pair, and focus group interviews held between August 2018 and November 2019. …”
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Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline by HongYi Li, Jun-Fen Fu, Andre Python

“…Most LLMs with multimodal abilities are closed-source models and, therefore, lack of transparency, model customization, and fine-tuning for specific clinical tasks and may also pose challenges regarding data protection and privacy, which are common requirements in clinical settings. …”
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Advancing Mental Health Care: A Comprehensive Review of Digital Tools and Technologies for Enhancing Diagnosis, Treatment, and Wellness by Muhammad Khalid Anser, Agha Amad Nabi, Ishfaq Ahmad, Muhammad Moinuddin Qazi Abro, Khalid Zaman

“…Exposure therapy for anxiety and trauma is increasingly using virtual reality environments. Although digital mental health therapies face challenges in relation to data privacy, limited long‐term efficacy, and technological inequality, digital technologies are modernizing mental healthcare. …”
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Syntactic Analysis of Spatial Structure Characteristics of Traditional Villages Along the Yellow River in Western Shanxi Province by Chenge GAO, Fang WANG

“…Villages with similar characteristics are classified into the same category, with the analysis of variance (ANOVA) being further used to explore the differences between these categories. …”
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Unveiling the Potential of Large Language Models in Transforming Chronic Disease Management: Mixed Methods Systematic Review by Caixia Li, Yina Zhao, Yang Bai, Baoquan Zhao, Yetunde Oluwafunmilayo Tola, Carmen WH Chan, Meifen Zhang, Xia Fu

“…A multifaceted approach that incorporates robust data security, domain-specific model fine-tuning, multimodal data integration, and wearables is crucial for the evolution of LLMs into invaluable adjuncts for health care professionals to transform chronic disease management. …”
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Comparing Artificial Intelligence–Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study by Kai Du, Ao Li, Qi-Heng Zuo, Chen-Yu Zhang, Ren Guo, Ping Chen, Wei-Shuai Du, Shu-Ming Li

“…MethodsThis 2-phase, double-blind, observational study used data from 50 patients previously enrolled in a registered randomized trial. …”
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Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review by Md Shofiqul Islam, Fahmid Al Farid, F. M. Javed Mehedi Shamrat, Md Nahidul Islam, Mamunur Rashid, Bifta Sama Bari, Junaidi Abdullah, Muhammad Nazrul Islam, Md Akhtaruzzaman, Muhammad Nomani Kabir, Sarina Mansor, Hezerul Abdul Karim

“…This article provides a meticulous and comprehensive review of imaging-based SARS-CoV-2 diagnosis using deep learning techniques up to May 2024. This article starts with an overview of imaging-based SARS-CoV-2 diagnosis, covering the basic steps of deep learning-based SARS-CoV-2 diagnosis, SARS-CoV-2 data sources, data pre-processing methods, the taxonomy of deep learning techniques, findings, research gaps and performance evaluation. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…For example, AI-driven analyses may reveal that regions with higher diabetes prevalence particularly benefit from targeted nutritional education programs, resulting in a 10% decrease in new diabetes cases.6Despite the promising advancements in AI applications within healthcare, it is essential to address ethical considerations and ensure data privacy during implementation. Establishing transparent policies, robust security protocols, and ethical guidelines is vital for safeguarding patient information and fostering trust in AI-driven solutions. …”
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Artificial intelligence and machine learning in acute respiratory distress syndrome management: recent advances by Songbei Li, Songbei Li, Ruiming Yue, Sen Lu, Jingchao Luo, Xiaoxiao Wu, Zhao Zhang, Mingzong Liu, Yuxin Fan, Yuxin Fan, Yuxuan Zhang, Yuxuan Zhang, Chun Pan, Xiaobo Huang, Hongli He

“…We explore diverse AI/ML applications, including early prediction and diagnosis using multi-modal data (electronic health records [EHR], imaging, ventilator waveforms), advanced prognostic assessment and risk stratification that outperform traditional scoring systems, and precise identification of ARDS subtypes to guide personalized treatment. …”
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Socioculturally Appropriate Internet-Based Geriatric Care Model for Older Adults Living With HIV: Experience-Based Co-Design Approach by Kristina M Kokorelias, Marina B Wasilewski, Dean Valentine, Andrew D Eaton, Erica Dove, Paige Brown, Stuart McKinlay, Christine L Sheppard, Esther Su, Hardeep K Singh, Ashley Flanagan, Alice Zhabokritsky, Reham Abdelhalim, Rabea Parpia, Rahel Zewude, Laura Jamieson, Sharon Walmsley, Luxey Sirisegaram

“…The process involved 3 phases: identifying needs through interviews and questionnaires, codeveloping a care model prototype through focus groups and a workshop, and refining the model using feedback from a world café format. Data were analyzed using thematic content analysis. …”
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Standardised and Objective Dietary Intake Assessment Tool (SODIAT): Protocol of a dual-site dietary intervention study to integrate dietary assessment methods [version 2; peer revi... by Katerina Petropoulou, Julie A Lovegrove, John Draper, Manfred Beckmann, Albert Koulman, Amanda J Lloyd, Benny Lo, George Mylonas, Stamatia Giannarou, Juliet Vickar, Adrian R Solis, Frank P.-W. Lo, Rosalind Fallaize, Jennifer Pugh, Isabel Garcia-Perez, Thomas Wilson, Michelle Weech, Eka Bobokhidze, Gary Frost

“…Urine and capillary blood samples were collected for biomarker analysis. Data analysis will assess dietary reporting accuracy across these methods using Lin’s concordance correlation coefficient. …”
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Community health fairs as experiential learning: a qualitative exploration of benefits and challenges by Martha Rojo, Scott Wright, Jing Jin, Erickson Feliciano, Margaret Love, Sharon Stevenson

“…Prior to the interview, all participants completed a demographic data sheet. All interviews were audio-recorded, transcribed, checked for accuracy, and de-identified, and MAXQDA was used to manage and code the interviews. …”
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Postpartum women’s prospective acceptability of long-acting HIV prevention approaches in Kenya: a qualitative study by Tessa Concepcion, John Kinuthia, Felix Abuna, Eunita Akim, Helen Aketch, Laurén Gómez, Grace John-Stewart, Bih Moki Suh, Emmaculate M Nzove, Nancy Ngumbau, Jerusha N Mogaka, Sarah Obatsa, Ben O Odhiambo, Caroline Omom, Marin Strong, Anjuli D Wagner, Salphine Watoyi, Jillian Pintye

“…Inductive and deductive content analysis was used, and themes of acceptability were explored using the Theoretical Framework of Acceptability (TFA). …”
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The Ethical Significance of Brain-Computer Interfaces as Enablers of Communication by Toma Gruica

“…For BCIs, this focus materializes in debates over whether to honor euthanasia requests (where legal) communicated through neural implants or concerns about data privacy and cognitive liberty. While these concerns are valid and urgent, they fail to capture the more “fundamental dimension,” which is how BCIs alter the conditions of moral personhood by restoring the capacity to communicate. …”
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The Efficacy of Conversational AI in Rectifying the Theory-of-Mind and Autonomy Biases: Comparative Analysis by Marcin Rządeczka, Anna Sterna, Julia Stolińska, Paulina Kaczyńska, Marcin Moskalewicz

“…Future research should focus on enhancing affective response mechanisms and addressing ethical concerns such as bias mitigation and data privacy to ensure safe, effective AI-based mental health support.…”
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A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification by Cheng-Jiang Wei, Yan Tang, Yang-Bai Sun, Tie-Long Yang, Cheng Yan, Hui Liu, Jun Liu, Jing-Ning Huang, Ming-Han Wang, Zhen-Wei Yao, Ji-Long Yang, Zhi-Chao Wang, Qing-Feng Li

“…To address privacy concerns, we utilized a lightweight deep neural network suitable for hospital deployment. …”
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Life-time experience of violence among women and girls living with disability in Nepal. by Padam Simkhada, Sapana Basnet, Shaurabh Sharma, Edwin van Teijlingen, Sharada Prasad Wasti, Tikadevi Dahal, Joshua Okyere, Ram Chandra Silwal, Manita Pyakurel

“…This was done by trained enumerators using the KoBo application on smartphones or tablets. …”
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