Preventive Care

Factors Influencing Delivery of Cancer Survivorship Care Plans: A National Patterns of Care Study.

Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved screening and treatments, the number of cancer survivors is reaching all-time highs. However, survivorship care plans (SCPs) are inconsistently used, denying many survivors access to critical information. This study used 46,408 SCPs generated from 2007 to 2016 and applied machine learning to identify...

Automatic detection of rare pathologies in fundus photographs using few-shot learning.

In the last decades, large datasets of fundus photographs have been collected in diabetic retinopathy (DR) screening networks. Through deep learning, these datasets were used to train automatic detectors for DR and a few other frequent pathologies, with the goal to automate screening. One challenge limits the adoption of such systems so far: automatic detectors ignore rare conditions that ophthalm...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerula...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by...

DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials.

Antimalarial drugs are becoming less effective due to the emergence of drug resistance. Resistance has been reported for all available malaria drugs, ...

Use of Artificial Intelligence-Based Analytics From Live Colonoscopies to Optimize the Quality of the Colonoscopy Examination in Real Time: Proof of Concept.

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Com...

Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm.

As many cases of atrial fibrillation (AF) are asymptomatic, patients often remain undiagnosed until complications (e.g. stroke) manifest. Risk-predic...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. Thi...

Stand-alone artificial intelligence - The future of breast cancer screening?

Although computers have had a role in interpretation of mammograms for at least two decades, their impact on performance has not lived up to expectati...

International evaluation of an AI system for breast cancer screening.

Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful. Despite the existence of...

Effect of experimental infectious bursal disease virus on clinical signs and pathogenesis of avian influenza virus HN in turkey by real time PCR.

Infectious bursal disease virus (IBDV) in turkeys may result in immunosuppression, and inability of turkeys to resist nonpathogenic or less pathogenic...

Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).

Breast cancer is one of the leading causes of cancer death among women in worldwide. Early diagnosis of breast cancer improves the chance of survival ...

Performance characteristics of an artificial intelligence based on convolutional neural network for screening conventional Papanicolaou-stained cervical smears.

BACKGROUND: The conventional Papanicolaou-stained cervical smear is the most common screening test for cervical cancer. The sensitivity of the test in...

Using machine learning models to improve stroke risk level classification methods of China national stroke screening.

BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in Chi...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical n...

An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.

: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial ...

Verification with the utility of an established rapid assessment of brain safety for newly developed vaccines.

In the twenty-first century, high contagious infectious diseases such as SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndr...

A novel artificial intelligence system for the assessment of bowel preparation (with video).

BACKGROUND AND AIMS: The quality of bowel preparation is an important factor that can affect the effectiveness of a colonoscopy. Several tools, such a...

Point-of-care cervical cancer screening using deep learning-based microholography.

Most deaths (80%) from cervical cancer occur in regions lacking adequate screening infrastructures or ready access to them. In contrast, most develope...