Explainable AI for Sensor Signal Interpretation to Revolutionize Human Health Monitoring: A Review by Abdullah S. Alharthi, Ahmed Alqurashi, Turki Essa Alharbi, Mohammed M. Alammar, Nasser Aldosari, Houssem R. E. H. Bouchekara, Yusuf A. Sha'aban, Mohammad Shoaib Shahriar, Abdulrahman Al Ayidh

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Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods by Carmina Liana Musat, Claudiu Mereuta, Aurel Nechita, Dana Tutunaru, Andreea Elena Voipan, Daniel Voipan, Elena Mereuta, Tudor Vladimir Gurau, Gabriela Gurău, Luiza Camelia Nechita

“…A literature review was conducted through searches in PubMed, Google Scholar, Science Direct, and Web of Science, focusing on studies from 2014 to 2024 and using keywords such as ‘artificial intelligence’, ‘machine learning’, ‘sports injury’, and ‘risk prediction’. While AI’s predictive power supports both team and individual sports, its effectiveness varies based on the unique data requirements and injury risks of each, with team sports presenting additional complexity in data integration and injury tracking across multiple players. …”
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Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

“…<b>Methods:</b> This paper presents a method that combines XAI techniques with a rigorous data-preprocessing pipeline to improve the accuracy and interpretability of ML-based diagnostic tools. …”
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AI-based virtual immunocytochemistry for rapid and robust fine needle aspiration biopsy diagnosis by Irfan Ahmed, Wei Zhang, Pikting Cheung, Vardhan Basnet, Zulfiqar Ali, May PY Tse, Fraser Hill, Tom Tak Lam Chan, Haibo Hu, Xinyue Li, Condon Lau

“…Abstract Presently, pathologists need to stain biopsy samples with standard and antibody-based immunocytochemistry (ICC) reagents for final diagnosis. …”
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AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta) by Annemiek Maaskant, Donghyeok Lee, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A. M. Langermans, Evgeni Levin

“…Evolving artificial intelligence (AI) technologies present opportunities for developing alternative methods. …”
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AI-2 Signaling: A Potential Driver of Bacteremia in Non-Typhoidal Salmonella Infections by Li Y, Lu B, Qiang X, Lin Y, He J, Cai Y

“…Collectively, these findings suggest that genes involved in the AI-2 pathway and biofilm-associated protein transport may be key factors contributing to the development of bacteremia in NTS infections.Keywords: invasive non-typhoidal Salmonella, whole genome sequencing, comparative genomics analysis, biofilm, quorum sensing, AI-2…”
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AI and Interventional Radiology: A Narrative Review of Reviews on Opportunities, Challenges, and Future Directions by Andrea Lastrucci, Nicola Iosca, Yannick Wandael, Angelo Barra, Graziano Lepri, Nevio Forini, Renzo Ricci, Vittorio Miele, Daniele Giansanti

“…Based on the overview, the integration of artificial intelligence (AI) in interventional radiology (IR) presents significant opportunities to enhance precision, efficiency, and personalization of procedures. …”
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Bringing AI to Clinicians: Simplifying Pleural Effusion Cytology Diagnosis with User-Friendly Models by Enrico Giarnieri, Elisabetta Carico, Stefania Scarpino, Alberto Ricci, Pierdonato Bruno, Simone Scardapane, Daniele Giansanti

“…AI-powered diagnostic systems have emerged as valuable tools in digital cytopathology. …”
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AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma by Haiting Cao, Xiaofeng Wu, Huayi Shi, Binbin Chu, Yao He, Houyu Wang, Fenglin Dong

“…In this work, we present a reliable tool to facilitate clinicians in the diagnosis of lymphoma. …”
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Trust and Acceptance Challenges in the Adoption of AI Applications in Health Care: Quantitative Survey Analysis by Janne Kauttonen, Rebekah Rousi, Ari Alamäki

“…MethodsWe collected and analyzed web-based survey data from 1100 Finnish participants, presenting them with 8 AI use cases in health care: 5 (62%) noninvasive applications (eg, activity monitoring and mental health support) and 3 (38%) physical interventions (eg, AI-controlled robotic surgery). …”
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AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…Techniques such as supervised and unsupervised learning, along with advanced approaches like Graph Neural Networks (GNNs), have proven particularly effective in detecting various types of financial fraud, including payment fraud, identity theft, and money laundering. This paper presents a comprehensive taxonomy of AI-driven fraud detection methodologies, synthesizing insights from a substantial number of research papers. …”
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Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review by Paul Notger Lempe, Camille Guinemer, Daniel Fürstenau, Corinna Dressler, Felix Balzer, Thorsten Schaaf

“…ObjectiveWe present a protocol for a scoping review of the literature on the implementation of generative AI in SR in the health care sector. …”
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Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study by Katie Ryan, Justin Hogg, Max Kasun, Jane Paik Kim

“… BackgroundThe increasing use of direct-to-consumer artificial intelligence (AI)–enabled mobile health (AI-mHealth) apps presents an opportunity for more effective health management and monitoring and expanded mobile health (mHealth) capabilities. …”
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Development and validation of AI-based automatic segmentation and measurement of thymus on chest CT scans by Yusheng Guo, Bingxin Gong, Guowei Jiang, Wang Du, Shuangfeng Dai, Qi Wan, Dongyong Zhu, Chanyuan Liu, Yi Li, Qing Sun, Qianqian Fan, Bo Liang, Lian Yang, Chuansheng Zheng

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AI-Enhanced Virtual Reality Self-Talk for Psychological Counseling: Formative Qualitative Study by ‪Moreah Zisquit, Alon Shoa, Ramon Oliva, Stav Perry, Bernhard Spanlang, Anat Brunstein Klomek, Mel Slater, Doron Friedman

“…This has sparked interest in conversational artificial intelligence (AI) agents as potential solutions. Despite this, the development of a reliable virtual therapist remains challenging, and the feasibility of AI fulfilling this sensitive role is still uncertain. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…To improve the interpretability of the leukemia detection process, explainable AI techniques, including Grad-CAM, Score-CAM, and Grad-CAM++, were integrated to vi-sualize critical regions influencing model predictions. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…In the healthcare industry, the ever-increasing volume of clinical trial data presents challenges for ensuring drug safety and detecting adverse drug reactions (ADRs). …”
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Successful Utilization of Mechanical Thrombectomy in a Presentation of Pediatric Acute Ischemic Stroke by Esther S. Kim, Erica K. Mason, Andrew Koons, Shawn M. Quinn, Robert L. Williams

“…Guidelines regarding the management of acute ischemic stroke (AIS) in the pediatric population using mechanical recanalization procedures are lacking. …”
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Integrated artificial intelligence in healthcare and the patient’s experience of care by Oluwatosin Ogundare, Tolu Owadokun, Temitope Ogundare, Promise Ekpo, Ha Linh Nguyen, Stephen Bello

“…In this regard, we present empirical analysis of thematic concerns that affect patients within AI integrated healthcare systems and how the experience of care may be influenced by the degree of AI integration. …”
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Ethical framework for responsible foundational models in medical imaging by Debesh Jha, Gorkem Durak, Abhijit Das, Jasmer Sanjotra, Onkar Susladkar, Suramyaa Sarkar, Ashish Rauniyar, Nikhil Kumar Tomar, Linkai Peng, Sirui Li, Koushik Biswas, Ertugrul Aktas, Elif Keles, Matthew Antalek, Zheyuan Zhang, Bin Wang, Xin Zhu, Xin Zhu, Hongyi Pan, Deniz Seyithanoglu, Alpay Medetalibeyoglu, Vanshali Sharma, Vedat Cicek, Amir A. Rahsepar, Rutger Hendrix, Rutger Hendrix, A. Enis Cetin, Bulent Aydogan, Mohamed Abazeed, Frank H. Miller, Rajesh N. Keswani, Rajesh N. Keswani, Hatice Savas, Sachin Jambawalikar, Daniela P. Ladner, Amir A. Borhani, Concetto Spampinato, Concetto Spampinato, Michael B. Wallace, Michael B. Wallace, Ulas Bagci

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