GitHub

Welcome the Era of One-shot Long-horizon Parsing.

torch==2.10.0 torchvision==0.25.0 transformers==4.57.1 Pillow==12.1.1 matplotlib==3.10.8 einops==0.8.2 addict==2.4.0 easydict==1.13 pymupdf==1.27.2.2 psutil==7.2.2 Set up the environment (uv-managed ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
openheart.bmj

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Nature

Machine learning-based prediction of primary aldosteronism subtype using comprehensive clinical features

Primary aldosteronism (PA) has two major subtypes: unilateral (uPA) and bilateral (bPA). Although several diagnostic models for subtype classification have been reported, the optimal combination of ...
Scientific Research Publishing

Comparative Analysis of ML Models for Survival Prediction of Glioblastoma ()

1 Department of Biochemistry, Chemistry, and Geology, Minnesota State University, Mankato, Mankato, MN, USA. 2 Department of Computer Information Science, Minnesota ...
LinkedIn

Estimating Sales with Multiple Linear Regression: From Math to Python with Solve

Modeling marketing and pricing decisions based on historical data is one of the most efficient ways to guide business strategies. This article shows how statistics and programming work together to ...
LinkedIn

SHAP with Python (Code and Explanations)

In contemporary machine learning workflows, interpretability has emerged as a critical requirement. As models grow in complexity, understanding how individual features contribute to a model’s ...
Frontiers

Interpretable prediction of stroke prognosis: SHAP for SVM and nomogram for logistic regression

Ischemic Stroke (IS) stands as a leading cause of mortality and disability globally, with an anticipated increase in IS-related fatalities by 2030. Despite therapeutic advancements, many patients ...
Frontiers

The Preprocessed Connectomes Project Quality Assessment Protocol - a resource for measuring the quality of MRI data.

Background: Although several measures have been proposed for assessing the quality of structural and fMRI data, there is no clear guidance on which of the measures are the best indicators of quality, ...
Nature

Hybrid machine learning approach for landslide prediction, Uttarakhand, India

Natural disasters always have a damaging effect on our way of life. Landslides cause serious damage to both human and natural resources around the world. In this paper, the prediction accuracy of five ...