Application of federated learning in predicting breast cancer by Chai Jiarui

“…The prediction and diagnosis of breast cancer relies on multimodal data, such as imaging, genetic information, and patient lifestyle habits. …”
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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

“…This study aimed to develop and validate several predictive models for non-adherence, using patient-reported data collected via a structured questionnaire. …”
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The Prediction of the Compaction Curves and Energy of Bituminous Mixtures by Filippo Giammaria Praticò, Giusi Perri

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Comparing prediction efficiency in the BTW and Manna sandpiles by Denis Sapozhnikov, Alexander Shapoval, Mikhail Shnirman

“…The existence of the inactivity allows for the prediction of these events in advance. In this work, we explore the predictability of the Bak–Tang–Wiesenfeld (BTW) and Manna models on the square lattice as a function of the lattice length. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
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Machine Learning with Voting Committee for Frost Prediction by Vinícius Albuquerque de Almeida, Juliana Aparecida Anochi, José Roberto Rozante, Haroldo Fraga de Campos Velho

“…A machine learning (ML)-based methodology for predicting frosts was applied to the southern and southeastern regions of Brazil, as well as to other countries including Uruguay, Paraguay, northern Argentina, and southeastern Bolivia. …”
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Predicting surgical risk in morbidly obese patients by K. A. Anisimova, D. I. Vasilevsky, S. G. Balandov, E. T. Berulava, A. V. Zinchenko, N. V. Markov, I. G. Buhankov, E. V. Blinov, G. V. Semikova

“…The results obtained during the study made it possible to integrate the developed tactics of preoperative examination and preparation for surgical intervention in morbidly obese patients into a practical algorithm. Application of the developed tools for predicting the risk of complications in bariatric surgeries allowed to reduce the complication rate from 12.2 % to 2.0 %, and the mortality rate from 2.0 % to 0 %.CONCLUSION. …”
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Machine Learning for Health Insurance Prediction in Nigeria by Victor Enemona Ochigbo, Oluwasogo Adekunle Okunade, Emmanuel Gbenga Dada, Oluyemi Mikail Olaniyi, Oluwatoyosi Victoria Oyewande

“…This paper focused on predicting the likelihood of medical insurance coverage among individuals in Nigeria by employing four prominent Machine learning techniques: Logistic Regression, Random Forest, Decision Tree, and Support Vector Machine classifiers. …”
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Population FBA predicts metabolic phenotypes in yeast. by Piyush Labhsetwar, Marcelo C R Melo, John A Cole, Zaida Luthey-Schulten

“…We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen), while FBA without proteomics constraints predicts respirative metabolism almost exclusively. …”
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STEP-BY-STEP PREDICTION OF LATE SPONTANEOUS MISCARRIAGE by Юлия Алексеевна Дударева, Татьяна Викторовна Раченкова, Сергей Вадимович Дронов

“…The aim of the study was to develop a step-by-step system for predicting late spontaneous miscarriages, taking into account clinical, anamnestic, echographic data, and the cytokine status of pregnant women. …”
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Prediction models for COVID-19 disease outcomes by Cynthia Y. Tang, Cheng Gao, Kritika Prasai, Tao Li, Shreya Dash, Jane A. McElroy, Jun Hang, Xiu-Feng Wan

“…Using the Virus-Human Outcomes Prediction (ViHOP) algorithm, we aim to utilize the individual’s clinical characteristics, the individual’s location, and the infecting SARS-CoV-2 virus characteristics obtained by whole genome sequencing to determine their likelihood of admission to the hospital, admission to the intensive care unit (ICU), or experiencing long COVID. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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The development of individual content educational courses composition algorithms genetic operators by Belomoytsev D.E.

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ALGORITHMS OF PSYCHOLOGICAL EDUCATION AND SUPPORT OF MEDICAL WORKERS DURING THE WAR IN UKRAINE by Lydia V. Butska, Hanna B. Varina, Oksana O. Drevitska, Valentin O. Ryzhak, Volodymyr I. Bulda, Olha V. Kovalova

Subjects: “…psychological medical education…”
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Advanced predictive analytics for bio-waste management using YOLOv8-SPP to enhance waste prediction and sustainability in smart cities by Selvalakshmi Balasubramanium, Bharathiraja Nagu, Shonak Bansal, Mohammad Rashed Iqbal Faruque, Kholoud Saad Al-mugren

“…This research suggests a new predictive analytics model using the YOLOv8-SPP algorithm for improved waste management. …”
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Prediction of 1-year post-operative mortality in elderly patients with fragility hip fractures in China: evaluation of risk prediction models by Qiyuan Lu, Mengmeng Chen, Houfu Ling

“…This investigation conducts a comparative evaluation of seven prognostic models—the Sernbo Score, Jiang et al. model, Nottingham Hip Fracture Score (NHFS), Holt et al. algorithm, HEMA, ASAgeCoGeCC Score, and SHiPS—HiPSe, and SHire, and SHim, HEMA, ham Hip Fracture Score (mortality risk prediction in elderly fragility hip fracture patientsMethodsIn this retrospective cohort analysis, all consecutive patients aged isk prediction in elderly fragility hip fracture between January 2018 and October 2022 were enrolled. …”
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An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach by I. Elzein, Yu. N. Petrenko

“…This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. …”
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ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias by Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng

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Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

“…This study evaluates two log-based methodologies for specific surface modeling and their role in predicting permeability. The first method utilizes density and gamma-ray logs, as previously validated in North Sea chalks, while the second method innovatively integrates deep resistivity and porosity data using a K-nearest neighbor machine learning algorithm. …”
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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

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