A combination of quantitative and qualitative methods in investigating risk factors for lost to follow-up for tuberculosis treatment in Japan - Are physicians and nurses at a parti... by Lisa Kawatsu, Kazuhiro Uchimura, Akihiro Ohkado, Seiya Kato

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Revolutionizing Midwifery Education : A Scoping Review of Artificial Intelligence Methods by Harridhil Silmi, Ari Indra Susanti

“…Despite these advancements, challenges such as ethical concerns (algorithmic bias, privacy issues), poor data quality, limited AI expertise among educators, and resistance to change in traditional learning environments were noted. …”
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Estimation of the Ultimate Bearing Capacity of the Rocks via Utilization of the AI-Based Frameworks by Bianca Damico, Matteo Conti

“…The approach adopted here is new and solves the problem using KNN combined with two modern nature-inspired optimization frameworks, namely the Honey Badger Algorithm (HBA) and Equilibrium Slime Mould Algorithm (ESMA). …”
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The ARTificial revolution. Introducing generative artificial intelligence tools into artistic education by Andrés Torres-Carceller

“…The aim of combining AI algorithms with traditional image editing techniques is not only to teach instrumental skills but also to foster a critical understanding of the limitations and risks associated with these technologies, promoting responsible and ethical use. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. …”
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Influencing factors of occupational injury in construction workers of European Union based on Boruta algorithm and logistic regression by Zhian LI, Lin ZHANG, Peng ZHANG, Xiaojun ZHU

“…A total of 25 variables in the dimensions of psychosocial risk, use of digital technology, health status, and preventive measures at the workplace were extracted after Chi-square test, and then a combination of Boruta's algorithm and logistic regression was applied to identify the key factors affecting occupational injuries. …”
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Reconsidering the use of race, sex, and age in clinical algorithms to address bias in practice: A discussion paper by Reanna Panagides, Jessica Keim-Malpass

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A multiobjective evolutionary algorithm incorporating neighborhood detection for the vehicle routing problem with soft time windows by Hao Jiang, Zhiwei Zhang, Chao Wang, Xiaoshu Xiang

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Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey by Karthik Ramesh, BS, Aaron Boussina, PhD, Supreeth P. Shashikumar, PhD, Atul Malhotra, MD, Christopher A. Longhurst, MD, MS, Christopher S. Josef, MD, Kimberly Quintero, RN, MS, Jake Del Rosso, MD, Shamim Nemati, PhD, Gabriel Wardi, MD, MPH

“…COnformal Multidimensional Prediction Of SEpsis Risk (COMPOSER), a deep learning algorithm, is used at two EDs of a large academic medical center to predict sepsis before clear clinical presentation. …”
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ANALYSIS AND ASSESSMENT OF FINANCIAL AND BUSINESS ACTIVITIES TO MINIMIZE TAX RISKS OF COMPANIES by E. V. Lyuter, Y. V. Gusarova, M. M. Starkova, A. Yu. Klonitskaya

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Utilising AI technique to identify depression risk among doctoral students by Changhong Teng, Chunmei Yang, Qiushi Liu

“…Based on the data from the 2019 Nature Global Doctoral Student Survey, we first screened 13 highly relevant features from a total of 37 features potentially related to the risk of depression among doctoral students by Random Forest algorithm. …”
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RISK FACTORS OF ARRHYTHMIAS IN PATIENTS WITH ACUTE DECOMPENSATION OF CHRONIC HEART FAILURE by N. V. Larionova, A. M. Shutov, M. V. Menzorov, E. V. Efremova, V. V. Kasalinskaya

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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

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RISKS OF IMPLEMENTING AND USING ARTIFICIAL INTELLIGENCE BY OIL AND GAS SECTOR ENTERPRISES by V.B. Kochkodan, M.Yu. Petryna

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Methodology of risks assessment of information security evaluation in e-economy systems by L. M. Lynkov, T. N. Beliatskaya, V. S. Knyazkova

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Sudden Infant Death Syndrome: Definition Evolution, Epidemiology and Risk Factors by Natalya N. Korableva

“…This algorithm is proposed to be used in educational programs for pregnant women and parents of infants.…”
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Addressing the Ethical, Legal, and Social Issues of Healthtech in Education: Insights From Japan by Motofumi Sumiya, Tomoko Nishimura, Kyoko Aizaki, Ikue Hirata, Nobuaki Tsukui, Yuko Osuka, Manabu Wakuta, Atsushi Senju

“…The study underscores the need for a multifaceted approach to mitigate risks such as data misuse, inequitable access, and algorithmic bias, ensuring the ethical and effective use of healthtech in education. …”
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Revolutionizing Education: Harnessing Machine Learning and Deep Learning for Digital Examination Transformation by Shilpi Gautam, Asadi Srinivasulu

“…The digital examination process entails the collection and secure storage of sensitive student data, raising worries about potential data security breaches and violations of privacy. To mitigate these risks, the proposed system aims to implement robust fairness-aware assessment algorithms while also incorporating advanced encryption and privacy-preserving techniques. …”
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Assessing the Current Limitations of Large Language Models in Advancing Health Care Education by JaeYong Kim, Bathri Narayan Vajravelu

“…This study aims to evaluate the application of state-of-the-art LLMs in health care education, highlighting the following shortcomings as areas requiring significant and urgent improvements: (1) threats to academic integrity, (2) dissemination of misinformation and risks of automation bias, (3) challenges with information completeness and consistency, (4) inequity of access, (5) risks of algorithmic bias, (6) exhibition of moral instability, (7) technological limitations in plugin tools, and (8) lack of regulatory oversight in addressing legal and ethical challenges. …”
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Evidence, Guidelines and Treatment Algorithms for Patients with Arterial Hypertension and Dyslipidemia: the Need for Compromise and Optimization of Tactics in Practical Healthcare by O. M. Drapkina, M. V. Ezhov, S. R. Gilyarevsky, R. N Shepel

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