Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…The aim of the study is to use machine learning techniques to develop predictive models that may be used to evaluate methylene blue dye degradation capacity in contaminated water. …”
Get full text

Hemorrhage risk associated with triple antithrombotic therapy: a focused real-world pharmacovigilance disproportional analysis study by Kannan Sridharan, Gowri Sivaramakrishnan

“…Signal detection used both frequentist (reporting odds ratio [ROR], proportional reporting ratio and Bayesian (Bayesian Confidence Propagation Neural Network, Multi-Item Gamma Poisson Shrinker algorithms. The lower limit of 95% confidence interval of ROR above 1 indicates higher reporting risk of bleeding. …”
Get full text

Nasolacrimal Duct Obstruction Secondary to Radioactive Iodine-131 Therapy for Differentiated Thyroid Cancer by A. A. Trukhin, V. D. Yartsev, M. S. Sheremeta, D. V. Yudakov, M. O. Korchagina, R. Kh. Salimkhanov, S. V. Grishkov

“…Deterministic effects of medical exposure to ionising radiation can be associated with both the effectiveness of treatment and adverse drug reactions to it. The latter may drastically deteriorate the quality of life of a patient after radionuclide therapy. …”
Get full text

Copper Metabolism-Related Genes as Biomarkers in Colon Adenoma and Cancer by Zhang T, Fu Y

“…These genes correlate with immune infiltration and may serve as diagnostic and therapeutic targets. …”
Get full text

Comparative Assessment of the Dynamics of Visual Performance of a Patient with Visually Intense Work with Binocular Cataract after Various Technologies of Cataract Phacoemulsificat... by D. F. Pokrovsky, I. B. Medvedev, N. I. Ovechkin, I. G. Ovechkin, A. I. Pavlov

“…It has been determined that with an increase in the level of complexity of the ophthalmo-ergonomic tests presented (“signal-response”; “selection of a signal from several — response”; “selection of a signal in conditions of time pressure”), there is a corresponding increase in the difference in the level of SR between groups of patients who were maISBCS and trISBCS, were performed (by 1.5 %, p > 0.05; 16.1 %, p < 0.05; and 22.1 %, p < 0.05, respectively), which may be associated with the occurrence of postoperative anisometropia.…”
Get full text

A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students by Flórián Gubics, Ádám Nagy, József Dombi, Antónia Pálfi, Zoltán Szabó, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

Get full text

Study on Discrete Null-Field Equation Methods for Bounded Simply Connected Domains: Better Locations of Source Nodes by Li-Ping Zhang, Zi-Cai Li, Hung-Tsai Huang, Ming-Gong Lee, Alexander L. Kazakov

“…The development of algorithms based on the NFE lags far behind that of the traditional boundary element method (BEM). …”
Get full text

Digital remote monitoring of people with multiple sclerosis by Michelangelo Dini, Michelangelo Dini, Giancarlo Comi, Letizia Leocani, Letizia Leocani, Letizia Leocani

“…We focus on tools and techniques applied to data from wearable sensors, smartphones, and other connected devices, as well as AI-based methods for the analysis of big data.ResultsWearable sensors and machine learning algorithms show significant promise in monitoring motor symptoms, such as fall risk and gait disturbances. …”
Get full text

New Challenging Systemic Therapies for Juvenile Scleroderma: A Comprehensive Review by Chiara Sassetti, Claudia Borrelli, Martha Mazuy, Cristina Guerriero, Donato Rigante, Susanna Esposito

“…While jLS predominantly affects the skin and subcutaneous tissues, jSS may involve multiple internal organs and is associated with increased morbidity and mortality. …”
Get full text

An interpretable machine learning approach for predicting and grading hip osteoarthritis using gait analysis by Qing Yang, Xinyu Ji, Yuyan Zhang, Shaoyi Du, Bing Ji, Wei Zeng

“…Gait analysis provides objective data on the patient’s walking pattern and can detect subtle changes in gait that may not be apparent on a radiographic image. Trial registration ClinicalTrials. gov (NCT01907503). …”
Get full text

Will AI “Subtly” Take Over Decision-making in the EU Migration Context? Warnings and Lessons from ETIAS and VIS by Lorenzo Gugliotta, Abdullah Elbi

“…As a result, the ETIAS and VIS processing may progressively reduce the extent to which human caseworkers review and question the AI-generated recommendations. …”
Get full text

AI-Based Performance Classification of Multi-Level System-of-Systems via Hypergraph Modeling by Jun Jiang, Abdeslem Smahi, Yiwen Chen, Othman Lakhal, Rochdi Merzouki

“…Without clear classifications, engineers may struggle to assess the severity of malfunctions and implement timely corrective actions. …”
Get full text

Comparative analysis of force sensitive resistor circuitry for use in force myography systems for hand gesture recognition by Giancarlo K. Sagastume, Peyton R. Young, Marcus A. Battraw, Justin G. Kwong, Jonathon S. Schofield

“…Further, contemporary machine learning algorithms used to detect hand gestures were unaffected by the circuitry employed. …”
Get full text

Spatial and Temporal Expansion of Photovoltaic Sites and Thermal Environmental Effects in Ningxia Based on Remote Sensing and Deep Learning by Heao Xie, Peixian Li, Fang Shi, Chengting Han, Ximin Cui, Yuling Zhao

“…Localized cooling patterns may be influenced by albedo and vegetation dynamics, though further validation is needed. …”
Get full text

Impacts of climate change on the global spread and habitat suitability of Coxiella burnetii: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat, Niloufar Lorestani, Farzin Shabani

“…Materials and methods: An ensemble species distribution modelling approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”
Get full text

Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning by Chao Lin, Yue Wan, Yong Xu, Qingsong Zou, Xiaoxiao Li

“…Machine learning (ML) algorithms identified feature genes of OA-macrophages. …”
Get full text

Clarification of Degraded Neutron Radiographic Images and Its Quality Metric Method by ZHANG Tian, MENG Chengbo, ZHANG Zhen, ZHAO Chenyi, QIAO Shuang

“…Suppressing some single distortion may introduce or aggravate other kinds of distortions. …”

Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

“…Aggregatibacter actinomycetemcomitans and Fusobacterium nucleatum may also play a role in the development of Alzheimer's disease. …”
Get full text

Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review by Wilson W S Tam, Kang Sim, Jing Ling Tay, Yun Ling Ang

“…Future machine learning studies may want to focus on the inclusion of a broader swathe of variables including ecological momentary assessments, with a greater amount of good quality big data covering longer longitudinal illness courses and coupled with external validation of study findings.PROSPERO registration number The review was registered on PROSPERO, ID: CRD42023441108.…”
Get full text

An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…Machine learning (ML) approaches have emerged as a promising technique to predict structural similarity from MS/MS that may surpass the current state-of-the-art algorithmic methods. …”
Get full text