Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that ma...

Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.

: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 millio...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

[Applications of artificial intelligence to new drug development].

Artificial intelligence (AI) encompasses technologies recapitulating four dimensions of human intell...

Associated factors of white matter hyperintensity volume: a machine-learning approach.

To identify the most important parameters associated with cerebral white matter hyperintensities (WM...

Detection of Referable Horizontal Strabismus in Children's Primary Gaze Photographs Using Deep Learning.

PURPOSE: This study implements and demonstrates a deep learning (DL) approach for screening referabl...

Using Domain-Specific Fingerprints Generated Through Neural Networks to Enhance Ligand-Based Virtual Screening.

Similarity-based virtual screening is a fundamental tool in the early drug discovery process and rel...

A deep learning-based model for screening and staging pneumoconiosis.

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pne...

Screening of Alzheimer's disease by facial complexion using artificial intelligence.

Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive...

Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer.

Determining the etiologic basis of the mutations that are responsible for cancer is one of the funda...

Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.

Our previous research shows that structured cancer DX description data accuracy varied across electr...

Using Natural Language Processing and Machine Learning to Identify Hospitalized Patients with Opioid Use Disorder.

Opioid use disorder (OUD) represents a global public health crisis that challenges classic clinical ...

Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.

BACKGROUND AND OBJECTIVE: The new type of Coronavirus (2019-nCov) epidemic spread rapidly, causing m...

Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review.

With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researche...

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review.

Diabetes mellitus, commonly measured through an invasive process which although is accurate, has man...

Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews.

BACKGROUND AND OBJECTIVE: To examine whether the use of natural language processing (NLP) technology...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

The increased prevalence of childhood obesity is expected to translate in the near future into a con...

Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis.

BACKGROUND: The impending scale up of noncommunicable disease screening programs in low- and middle-...

Exploration of text matching methods in Chinese disease Q&A systems: A method using ensemble based on BERT and boosted tree models.

BACKGROUND: Text matching is one of the basic tasks in the field of natural language processing. Owi...

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