Green vehicle routing optimization based on dynamic constraint selection co-evolutionary algorithm by Lu-jie Zhou, Hai-fei Zhang, Jun-hao Fu

“…The algorithm treats the complete problem model as a complex task and introduces a shift crowding distance calculation that considers both individual distribution and convergence information when solving this complex task, effectively balancing the convergence and diversity of solutions. …”
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Pasireotide-induced hyperglycemia in Cushing’s disease and Acromegaly: A clinical perspective and algorithms proposal by Przemysław Witek, Marek Bolanowski, Adam Krętowski, Aleksandra Głowińska

“…Moreover, pasireotide used in the treatment of CD may lead to more frequent and difficult-to-treat glycemic disorders than those observed in acromegaly. …”
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Fitting Penalized Estimator for Sparse Covariance Matrix with Left-Censored Data by the EM Algorithm by Shanyi Lin, Qian-Zhen Zheng, Laixu Shang, Ping-Feng Xu, Man-Lai Tang

“…To address this issue, we treat censored data as a special case of incomplete data and employ the Expectation Maximization algorithm combined with the coordinate descent algorithm to efficiently fit the two penalized estimators. …”
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Designing and validating a clinical decision support algorithm for diabetic nephroprotection in older patients by Simon LeClerc, Nicolas Fernandez, Kelley Kilpatrick, Cheryl Sadowski, Noor Alsalemi, Naoual Elftouh, Jean-Philippe Lafrance, Sherilyn Houle

“…The aim of this research is to design and validate a CDS algorithm for prescribing renin-angiotensin-aldosterone system inhibitors (RAASi) for older patients with diabetes.Methods The design of the CDS tool included the following phases: (1) gathering evidence from systematic reviews and meta-analyses of randomised clinical trials to determine the number needed to treat (NNT) and time-to-benefit (TTB) values applicable to our target population for use in the algorithm. (2) Building a list of potential cases that addressed different prescribing scenarios (starting, adding or switching to RAASi). (3) Reviewing relevant guidelines and extracting all recommendations related to prescribing RAASi for DKD. (4) Matching NNT and TTB with specific clinical cases. (5) Validating the CDS algorithm using Delphi technique.Results We created a CDS algorithm that covered 15 possible scenarios and we generated 36 personalised and nine general recommendations based on the calculated and matched NNT and TTB values and considering the patient’s life expectancy and functional capacity. …”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…Therefore, we propose MTEPN as an innovative deep convolutional neural network algorithm specifically designed to perform multiple visual tasks concurrently. …”
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Explainable machine learning model and nomogram for predicting the efficacy of Traditional Chinese Medicine in treating Long COVID: a retrospective study by Jisheng Zhang, Yang Chen, Aijun Zhang, Yi Yang, Liqian Ma, Hangqi Meng, Jintao Wu, Kean Zhu, Jiangsong Zhang, Ke Lin, Xianming Lin

“…Data from 1,204 patients served as the training set, while 127 patients formed the testing set.ResultsWe employed five ML algorithms: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Neural Network (NN). …”
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Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy. by Andres Portocarrero-Bonifaz, Salman Syed, Maxwell Kassel, Grant W McKenzie, Vishwa M Shah, Bryce M Forry, Jeremy T Gaskins, Keith T Sowards, Thulasi Babitha Avula, Adrianna Masters, Jose G Schneider, Scott R Silva

“…Advances in computation, algorithms, and data availability have popularized the use of machine learning to predict patient outcomes. …”
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PD-L1 expression as a negative predictive biomarker in advanced esophageal squamous-cell cancer treated with chemotherapy alone by M. Sachdeva, J.J. Zhao, K.X. Zhu, D.T.W. Yap, N.Z.H. Wong, N.B. Kumarakulasinghe, J. Tey, R. Sundar

“…This study aims to determine the prognostic significance of PD-L1 expression in patients treated with first-line chemotherapy alone in aESCC. …”
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State update algorithm for associative elastic-plastic pressure-insensitive materials by incremental energy minimization by N.A. Nodargi, E. Artioli, F. Caselli, P. Bisegna

“…This work presents a new state update algorithm for small-strain associative elastic-plastic constitutive models, treating in a unified manner a wide class of deviatoric yield functions with linear or nonlinear strain-hardening. …”
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State update algorithm for associative elastic-plastic pressure-insensitive materials by incremental energy minimization by N.A. Nodargi, E. Artioli, F. Caselli, P. Bisegna

“…This work presents a new state update algorithm for small-strain associative elastic-plastic constitutive models, treating in a unified manner a wide class of deviatoric yield functions with linear or nonlinear strain-hardening. …”
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Postoperative Respiratory Depression Associated with Pregabalin: A Case Series and a Preoperative Decision Algorithm by Naveen Eipe, John Penning

“…Pregabalin is gaining popularity in the perioperative period for its usefulness in treating neuropathic pain and its apparent opioid-sparing effect. …”
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Enhanced Heart Disease Diagnosis Using Machine Learning Algorithms: A Comparison of Feature Selection by Hirmayanti, Ema Utami

“…So in this study, it will be more focused on the selection of relevant features or attributes to increase the accuracy value of the Machine Learning algorithm. The algorithms used include Random Forest and SVM. …”
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Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Papillary Thyroid Carcinoma Variants by Sakhr Alshwayyat, Haya Kamal, Owais Ghammaz, Tala Abdulsalam Alshwayyat, Mustafa Alshwayyat, Ramez M. Odat, Hamdah Hanifa, Wafa Asha, Nesreen A. Saadeh

“…Methods Chi‐square tests, Kaplan–Meier curves, log‐rank tests, and Cox regression were used. Five ML algorithms constructed prognostic models predicting 5‐year survival, validated using the AUC of the ROC curve. …”
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The Active and Reactive Power Generation Reduction Based on Optimal location of UPFC Based on Genetic Algorithm by Sana Khalid Abd Al Hassan, Firas Mohammed Tuaimah, Yasser Nadhum Abd, Ali Adil Al-Lami

“…This paper presents the effect of installing the UPFC on the Iraqi (400 kV) grid transmission system to control the active and reactive power flow by choosing the optimal location and parameters of Unified Power Flow Controllers (UPFCs), which were specified based on the Genetic Algorithm (GA) optimization method. The objectives are improving voltage profile, reducing power losses, treating power flow in overloaded transmission lines, and reducing power generation. …”
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DefogNet: A Single-Image Dehazing Algorithm with Cyclic Structure and Cross-Layer Connections by Suting Chen, Wenhao Fan, Shaw Peter, Chuang Zhang, Kui Chen, Yong Huang

“…In this paper, the novel Defog-SN algorithm is presented. This algorithm adds a spectral normalization layer to the discriminator’s convolution layer to make the discriminant network conform to a 1-Lipschitz continuum and further improve the model’s stability. …”
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Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy by Wu Tenghui, Liu Xinyi, Si Ziyi, Zhang Yanting, Ma Ziqian, Zhu Yiwen, Gan Ling

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Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials by Yougen Wu, Wenyu Zhu, Jing Wang, Lvwen Liu, Wei Zhang, Yang Wang, Jindong Shi, Ju Xia, Yuting Gu, Qingqing Qian, Yang Hong

“…Our aim was to build a machine learning‐based risk stratification model for predicting mortality in atezolizumab‐treated cancer patients. Methods Data from 2538 patients in eight atezolizumab‐treated cancer clinical trials across three cancer types (non‐small‐cell lung cancer, bladder transitional cell carcinoma, and renal cell carcinoma) were included. …”
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UPOINT System: A Diagnostic/Therapeutic Algorithm for Chronic Prostatitis/Chronic Pelvic Pain Syndrome by Phil Hyun Song

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Time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments by Peixin Wang, Youming Li, Shengming Chang, Xiaoping Jin, Xiaoli Wang

“…A novel time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments is proposed. …”
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