Overview of the cohort definition process. by Nicola Lazzarini (3528197)

Table_1_Optimal Reopening Pathways With COVID-19 Vaccine Rollout and Emerging Variants of Concern.pdf by Yanyu Xiao (682443)

Data_Sheet_1_Adaptive restraint design for a diverse population through machine learning.pdf by Wenbo Sun (531308)

Table_1_Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.docx by Jiajin He (13386702)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”

Data_Sheet_1_Accuracy of Deep Neural Network in Triaging Common Skin Diseases of Primary Care Attention.docx by Mara Giavina-Bianchi (11334102)

“…The triage process is usually conducted by primary care physicians; however, they may not be able to diagnose and assign the correct referral and level of priority for different dermatosis. …”

Table_1_Comparison and analysis of multiple machine learning models for discriminating benign and malignant testicular lesions based on magnetic resonance imaging radiomics.DOCX by Yanhui Feng (1484833)

Data_Sheet_1_A comprehensive analysis of genes associated with hypoxia and cuproptosis in pulmonary arterial hypertension using machine learning methods and immune infiltration ana... by Zuguang Chen (19743121)

Data_Sheet_1_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.pdf by Kiran J. McLoughlin (6442688)

Table_1_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.pdf by Kiran J. McLoughlin (6442688)

Table_2_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.xlsx by Kiran J. McLoughlin (6442688)

Table_1_A robust ensemble deep learning framework for accurate diagnoses of tuberculosis from chest radiographs.pdf by Xin Sun (127355)

Presentation_1_Feasibility of Dialysate Bolus-Based Absolute Blood Volume Estimation in Maintenance Hemodialysis Patients.pdf by Simon Krenn (9874167)

Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx by Xiaotong Sun (6535064)

Data_Sheet_1_Machine Learning Prediction Model for Acute Renal Failure After Acute Aortic Syndrome Surgery.docx by Jinzhang Li (9221930)

Table 1_The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients.docx by Zhou Liu (1506679)

“…Background<p>Acute upper gastrointestinal bleeding (AUGIB) is one of the most common critical diseases encountered in the intensive care unit (ICU), with a mortality rate ranging from 15 to 20%. …”

Table 1_Durable response of primary cardiac lymphoma after autologous stem cell transplantation and sequential CAR-T therapy: a case report and literature review.docx by Ge Wang (56838)

“…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”

Data Sheet 1_Durable response of primary cardiac lymphoma after autologous stem cell transplantation and sequential CAR-T therapy: a case report and literature review.pdf by Ge Wang (56838)

“…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”

DATASET AI by Elena Stamate (18836305)

“…</p><p dir="ltr">The primary aim of this dataset is to enable the development and validation of machine learning models for:</p><ul><li>Early identification of STEMI patients at high risk of developing cardiogenic shock;</li><li>Clinical triage optimization and prioritization for urgent angiography;</li><li>Supporting time-sensitive decision-making in resource-limited or overcrowded emergency settings.…”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”