Primary Care

Artificial intelligence in diabetic retinopathy: A natural step to the future.

Use of artificial intelligence in medicine in an evolving technology which holds promise for mass sc...

Use of Artificial Intelligence to Improve Diabetes Outcomes in Patients Using Multiple Daily Injections Therapy.

A Machine Learning Strategy for Autism Screening in Toddlers.

OBJECTIVE: Autism spectrum disorder (ASD) screening can improve prognosis via early diagnosis and in...

Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges.

Combinations of healthcare claims data with additional datasets provide large and rich sources of in...

[New Model for Intelligent Imaging Screening of Pulmonary Nodules].

The artificial intelligence based on medical aid diagnosis has been in full swing in these years. Ho...

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); how...

[Artificial intelligence in medicine-the wrong track or promise of cure?].

Artificial intelligence (AI) has attained a new level of maturity in recent years and is developing ...

Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice.

Artificial Intelligence (AI) and access to "Big Data" together with the evolving techniques in biote...

Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.

Although machine learning is increasingly being applied to support clinical decision making, there i...

High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of Staphylococcus aureus.

One potential source of new antibacterials is through probing existing chemical libraries for copper...

Discovery of Distinct Immune Phenotypes Using Machine Learning in Pulmonary Arterial Hypertension.

RATIONALE: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) an...

Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.

UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transform...

Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.

PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, ...

Correlation Network Analysis Provides Important Modules and Pathways for Human Hyperlipidemia.

Hyperlipidemia casts great threats to humans around the world. The systemic co-expression and functi...

Designing an Engineered Construct Gene Sensitive to Carbohydrate In-vitro and Candidate for Human Insulin Gene Therapy In-vivo.

Diabetes is a common disorder worldwide, and exhaustive efforts have been made to cure this disease....

Hydro-Ethanolic Extract of Ameliorates Total and Differential WBC, Lung Pathology and Oxidative Biomarkers in Asthmatic Rats.

The effects of ( ; PO) on total and differential WBC count, and oxidant/antioxidant biomarkers in b...

[The future of computer-aided diagnostics in chest computed tomography].

Recently, more and more attention has been paid to the utility of artificial intelligence in medicin...

DeepScreening: a deep learning-based screening web server for accelerating drug discovery.

Deep learning contributes significantly to researches in biological sciences and drug discovery. Pre...

Screening for Alzheimer's Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy.

BACKGROUND: Alzheimer's disease and related dementias (ADRDs) are being diagnosed at epidemic rates,...

Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) accounts for a significant proportion of lung cancer and ther...

Estimating Systolic Blood Pressure Using Convolutional Neural Networks.

Continuous blood pressure (BP) monitoring can produce a significant amount of digital data, which in...