Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel by Fariha Ahmed Nishat, M. F. Mridha, Istiak Mahmud, Meshal Alfarhood, Mejdl Safran, Dunren Che

“…It outperformed traditional diagnostic methods and other standalone machine learning algorithms, offering high accuracy and generalizability. …”
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The prognostic predictive value of indirect bilirubin-inflammation score in patients with nasopharyngeal carcinoma by JI Huojin, LI Jun, LUO Yonglin, QIN Weiling, YE Yinxin, CAI Yonglin

“…Results By comparing 14 types of machine learning algorithms, the optimal model, oblique random survival forest, was selected to construct IBI score. …”
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The role of artificial intelligence in managing hospitalized patients with mental illness: a scoping review by Md Samiun, Moustaq Karim Khan Rony, Sumaiya Yeasmin, Mia Md Tofayel Gonee Manik, Anupom Debnath, Mustakim Bin Aziz, Afia Fairooz Tasnim, Sadia Islam Nilima

“…Despite these advancements, challenges were noted, such as algorithmic biases due to non-diverse training data, privacy and security risks for sensitive patient information, and clinician resistance stemming from concerns about autonomy and ethical implications of AI-supported clinical decisions. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

“…Currently, none of the presented algorithms can meet the criteria of economic efficiency, even in the most developed countries. …”
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Remote clinical decision support tool for Parkinson’s disease assessment using a novel approach that combines AI and clinical knowledge by Harel Rom, Ori Peleg, Yovel Rom, Anat Mirelman, Gaddi Blumrosen, Inbal Maidan

“…This method represents a significant innovation, transforming clinical knowledge into practical algorithms that can serve as effective screening tools. …”
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A spike is a spike: On the universality of spike features in four epilepsy models by Armen Sargsyan, Pablo M. Casillas‐Espinosa, Dmitri Melkonian, Terence J. O'Brien, Gilles vanLuijtelaar

“…This fact may be used for the development of universal algorithms for seizure detection applicable to different rat models of epilepsy. …”
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Biochemical disturbances in schizophrenia — a «window of opportunity» by T. V. Zhilyaeva, A. S. Piatoikina, E. D. Kasyanov, G. V. Rukavishnikov, I. V. Semennov, O. V. Kostina, A. S. Blagonravova, G. E. Mazo

“…Moreover, screening algorithms for the detection and personalized correction of controlled biomarkers have not been introduced into clinical practice yet.   …”
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Adaptive strategies for the deployment of rapid diagnostic tests for COVID-19: a modelling study [version 2; peer review: 2 approved, 1 approved with reservations] by Emily Kendall, Lucia Cilloni, Nimalan Arinaminpathy, David Dowdy

“…Background Lateral flow assays (LFAs) for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provide an affordable, rapid and decentralised mean for diagnosing coronavirus disease 2019 (COVID-19). …”
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Comparison of Surface Current Measurement Between Compact and Square-Array Ocean Radar by Yu-Hsuan Huang, Chia-Yan Cheng

“…In Taiwan, the Taiwan Ocean Research Institute (TORI) has established a data quality management mechanism based on international standards for data filtering, noise reduction, and outlier detection, improving the accuracy and stability of radar-derived velocity measurements.To eliminate the effects caused by different center frequencies between MABT and KNTN, this study used the same algorithms and parameter settings as much as possible in all steps, from Doppler spectra processing to radial velocity calculation, ensuring the comparability of the data. …”
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INTEGRATED GRAPH-BASED TESTING PIPELINE FOR MODERN SINGLE-PAGE APPLICATIONS by Nataliia Golian, Varvara Tisheninova

“…Each tool is evaluated across five normalized dimensions − defect detection accuracy, execution speed, licensing or infrastructure cost, adoption effort, and scalability − weighted according to project priorities. …”
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Hemorrhage risk associated with triple antithrombotic therapy: a focused real-world pharmacovigilance disproportional analysis study by Kannan Sridharan, Gowri Sivaramakrishnan

“…Reports including combinations of DAPT (acetylsalicylic acid and clopidogrel) with oral anticoagulants (acenocoumarol, apixaban, dabigatran, edoxaban, rivaroxaban, and warfarin) were analyzed. 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. …”
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Optimization of energy acquisition system in smart grid based on artificial intelligence and digital twin technology by Zhen Jing, Qing Wang, Zhiru Chen, Tong Cao, Kun Zhang

“…The improved lightweight target detection model is combined to monitor the equipment status of the smart grid and extract key features. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…Our method applies residual connections with Squeeze-and-Excitation blocks along with hybrid attention systems and enhanced activation functions and optimization algorithms to boost gradient movement throughout feature extraction. …”
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MMLT: Efficient object tracking through machine learning-based meta-learning by Bibek Das, Asfak Ali, Suvojit Acharjee, Jaroslav Frnda, Sheli Sinha Chaudhuri

“…While Deep learning algorithms address these challenges, however, they typically require significant computational resources, exhibit high complexity, and demand large amounts of training data. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. …”
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Potential biomarkers and immune infiltration linking endometriosis with recurrent pregnancy loss based on bioinformatics and machine learning by Jianhui Chen, Qun Li, Xiaofang Liu, Fang Lin, Yaling Jing, Jiayan Yang, Lianfang Zhao

“…Protein-protein interaction (PPI) network and two machine learning algorithms were applied to identify the common core genes in both diseases. …”
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Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…The Zhurong rover of the Tianwen-1 mission has detected sulfates in its landing area. The analysis of these sulfates provides scientific evidence for exploring past hydration conditions and atmospheric evolution on Mars. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Ethically, this review surfaces critical issues, including algorithmic bias, data privacy concerns in mental health analytics, and the interpretability of black-box models used in outbreak surveillance. …”
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Transforming Manufacturing Quality Management with Cognitive Twins: A Data-Driven, Predictive Approach to Real-Time Optimization of Quality by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. …”
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