Primary Care

Preventive Care

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

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Predicting instructed simulation and dissimulation when screening for depressive symptoms.

The intentional distortion of test results presents a fundamental problem to self-report-based psych...

Malaria parasite detection and cell counting for human and mouse using thin blood smear microscopy.

Despite the remarkable progress that has been made to reduce global malaria mortality by 29% in the ...

Application of data mining methods to improve screening for the risk of early gastric cancer.

BACKGROUND: Although gastric cancer is a malignancy with high morbidity and mortality in China, the ...

Cirrus: An Automated Mammography-Based Measure of Breast Cancer Risk Based on Textural Features.

BACKGROUND: We applied machine learning to find a novel breast cancer predictor based on information...

Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance....

Calcitonin Screening in Nodular Thyroid Disease: Is There a Definitive Answer?

INTRODUCTION: Calcitonin (Ctn) is a hormone secreted by thyroid "C" cells and is considered an excel...

CbpM and CbpG of Streptococcus Pneumoniae Elicit a High Protection in Mice Challenged with a Serotype 19F Pneumococcus.

Among many pneumococcal antigens, choline-binding proteins (CPBs) display a high immunogenicity in a...

Immunogenicity of Concentrated and Purified Inactivated Avian Influenza Vaccine Formulation.

Avian influenza (AI) H9N2 is a low pathogenic virus subtype belonging to Orthomyxoviridae family. Gi...

Coreflood Study of Effect of Surfactant Concentration on Foam Generation in Porous Media.

The propagation of foam in an oil reservoir depends on the creation and stability of the foam in the...

Identification of Immune Signatures of Novel Adjuvant Formulations Using Machine Learning.

Adjuvants have long been critical components of vaccines, but the exact mechanisms of their action a...

Tox_(R)CNN: Deep learning-based nuclei profiling tool for drug toxicity screening.

Toxicity is an important factor in failed drug development, and its efficient identification and pre...

Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models.

The volume of high throughput screening data has considerably increased since the beginning of the a...

Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag).

Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- lear...

Bi-stream CNN Down Syndrome screening model based on genotyping array.

BACKGROUND: Human Down syndrome (DS) is usually caused by genomic micro-duplications and dosage imba...

Deep Learning-Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance.

TOPIC: Diagnostic performance of deep learning-based algorithms in screening patients with diabetes ...

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. In...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for scr...

Novel screening criteria for post-traumatic venous thromboembolism by using D-dimer.

AIM: Because severe trauma patients frequently manifest coagulopathy, it is extremely important to d...

Identifying in Palliative Care Consultations: A Tandem Machine-Learning and Human Coding Method.

Systematic measurement of conversational features in the natural clinical setting is essential to b...

Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data.

Machine learning has shown enormous potential for computer-aided drug discovery. Here we show how mo...

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