dDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, China ...

Cancer immunotherapy drugs known as immune checkpoint inhibitors (ICIs) can be miracle drugs for cancer patients, curing some and turning deadly disease into a manageable chronic condition in others.

Researchers developed and externally validated a machine learning model to predict the 28-day mortality risk in ICU patients with sepsis complicated by acute respiratory failure. Using routinely ...

Objective Atrial fibrillation (AF) screening by age achieves a low yield and misses younger individuals. We aimed to develop an algorithm in nationwide routinely collected primary care data to predict ...

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...

A new artificial intelligence model in the United States, SleepFM, has found that patterns in human slumber can be used to predict a person's risk for about 130 diseases, including dementia and ...

Bengaluru: Great Learning on Wednesday announced the launch of an AI in Healthcare programme in collaboration with Johns Hopkins University (JHU), one of the world’s top institutions in medicine and ...

In this project, a neural network model was built using Tensorflow. The model detects if a plant is suffering from a disease(Rust or Powdery Mildew). The model was ...

SINGAPORE – A new artificial intelligence (AI) system which will reduce the time required for a cardiac scan analysis and allow for faster diagnosis of coronary artery disease will be available at ...

1 Computer Science Department, Babcock University, Ilishan-Remo, Ogun State, Nigeria. 2 Computer Science Department, Adeleke University, Ede, Osun State, Nigeria. 3 Department of Applied Mathematics, ...

Abstract: The goal of the heart disease prediction project is to use machine learning and deep learning techniques to create an accurate and efficient system. To obtain insights into the dataset, the ...

Abstract: Our project introduces a groundbreaking approach to medical diagnostics through the development of a Multiple Diseases Prediction System leveraging the RCNN (recurrent and convolutional ...