Learning unbiased risk prediction based algorithms in healthcare: A case study with primary care patients by Vibhuti Gupta, Julian Broughton, Ange Rukundo, Lubna J. Pinky

“…Additionally, effective strategies are proposed to address gender, race, and age biases, ensuring that risk prediction outcomes are equitable and impartial. Through experiments with various machine learning algorithms leveraging the Fairlearn tool, we have identified biases in the dataset, compared the impact of these biases on the prediction performance, and proposed effective strategies to mitigate these biases. …”
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WCN25-867 BAYESIAN DEEP LEARNING ALGORITHMS TO PREDICT THE RATE OF DETERIORATION IN CHRONIC KIDNEY DISEASE by Laxmi Priya Kasi, Sujoy Kar, Sanjay Maitra, Tameem Ansari, Bharath Potla, Sangita Reddy

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Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea) by Degninou Yehadji, Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo

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PM2.5 concentration prediction using machine learning algorithms: an approach to virtual monitoring stations by Ahmad Makhdoomi, Maryam Sarkhosh, Somayyeh Ziaei

“…In this research, an attempt has been made to predict the concentrations of PM2.5 using four Machine Learning (ML) models. …”
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Use of responsible artificial intelligence to predict health insurance claims in the USA using machine learning algorithms by Ashrafe Alam, Victor R. Prybutok

“…Methods: Six ML algorithms were used to predict health insurance claims, and their performance was evaluated using various metrics. …”
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Leveraging Machine Learning Regression Algorithms to Predict Mechanical Properties of Evaporitic Rocks From Their Physical Attributes by Ayham Zaitouny, Hasan Arman, Anusuya Krishnan, Alaa Ahmed, Ahmed Gad

“…In this study, machine learning (ML) regression algorithms were applied to predict four key mechanical parameters, namely, uniaxial compressive strength (UCS), point load index (PLI), indirect tensile strength (ITS), and Schmidt hardness value (SHV), based on the physical attributes of evaporitic rocks. …”
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The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms by Hongxia Yan, Yixin Tan, Fan Qiao, Zhuotong Zeng, Yaqian Shi, Xueqin Zhang, Lu Li, Ting Zeng, Yi Zhan, Ruixuan You, Xinglan He, Rong Xiao, Xiangning Qiu

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Human-Centred Design Meets AI-Driven Algorithms: Comparative Analysis of Political Campaign Branding in the Harris–Trump Presidential Campaigns by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

“…Utilising a mixed-methods approach, we integrated quantitative analysis employing AI’s eye-tracking consumer behaviour metrics (Predict, trained on 180,000 screenings) with an AI-LLM neuroscience-based marketing assistant (CoPilot), with 67,429 areas of interest (AOIs). …”
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Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

“…Classification axioms can be formed by 1-class learning procedures for the predictive state evaluation of subsequent production start-ups based on collected machine and process data from past production start-ups. …”
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Coordinative Two-Stage Superheated Steam Temperature Linkage Control Based on Multivariable Generalized Predictive Control Algorithm by Sheng TONG, Le LIU, Pengfei WANG

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Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…A Bland-Altman plot of the differences between the predicted values and the assessment values showed 95% of them within 0.21 WTE per patient. …”
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Predictive Control for an Ankle Rehabilitation Robot Using Differential Evolution Optimization Algorithm-Based Fuzzy NARX Model by Shenglong Xie, Haiming Zhong, Yuntang Li, Su'an Xu, Wenyuan Liu, Shiyuan Bian, Shiwu Zhang

“…In this paper, based on differential evolution (DE) optimization algorithm and fuzzy nonlinear auto regressive with exogenous inputs (NARX) model, an iterative learning model predictive controller is constructed to achieve accurate and robust trajectory tracking control of an ankle rehabilitation robot driven by pneumatic muscle. …”
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FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

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Enhanced Robust Control of Induction Motor Using Combined Optimal Model Predictive Control With Super-Twisting Algorithm by REZGUI, S.-E., NEMOUCHI, B.

“…This paper presents a novel strategy for induction motor control that combines Optimal Model Predictive Control (OMPC) with the Super-Twisting Algorithm (STA) to enhance the performance of field-oriented control (IFOC) strategy under disturbances and uncertainties. …”
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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

“…To overcome these limitations, this paper proposes a novel energy scheduling framework that integrates the Model Predictive Control (MPC) with a Deep Reinforcement Learning algorithm, specifically the Deep Deterministic Policy Gradient (DDPG). …”
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Clean-Room Air Conditioning Control Based on Improved Min-Max Robust Model Predictive Control Algorithm by Qiang Luo, Ting Wang

“…Subsequently, an improved Min Max robust model predictive control algorithm was proposed to control the parameters of the model, and compared and analyzed with the original algorithm. …”
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Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms by Yuyang Chen, Jiansheng Zhong, Haixiang Li, Kunzhe Lin, Liangfeng Wei, Shousen Wang

“…Abstract This study aimed to predict arginine vasopressin deficiency (AVP-D) following transsphenoidal pituitary adenoma surgery using machine learning algorithms. …”
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Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning by Qingyun Wan, Kai Liu, Yuyang Bo, Xiya Yuan, Mufeng Li, Xiaoqiu Wang, Chuang Chen, Lanying Liu, Wenzhong Wu

“…To address this, an innovative machine learning algorithm, Relief-NDPGWO-WSVM, is developed to predict insomnia response to acupuncture. …”
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Prediction of the Immune Phenotypes of Bladder Cancer Patients for Precision Oncology by Hyuna Cho, Feng Tong, Sungyong You, Sungyoung Jung, Won Hwa Kim, Jayoung Kim

“…Bladder cancer (BC) is the most common urinary malignancy; however accurate diagnosis and prediction of recurrence after therapies remain elusive. …”
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