Preventive Care

Practical Model Selection for Prospective Virtual Screening.

Virtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the data set and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual screening on two protein-protein interactions, PriA-SSB and RMI-FANCM, and present ...

Microfluidic droplets content classification and analysis through convolutional neural networks in a liquid biopsy workflow.

In a recent paper we presented an innovative method of liquid biopsy, for the detection of circulating tumor cells (CTC) in the peripheral blood. Using microfluidics, CTC are individually encapsulated in water-in-oil droplets and selected by their increased rate of extracellular acidification (ECAR). During the analysis, empty or debris-containing droplets are discarded manually by screening image...

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 past 5 years, malaria is still a serious global he...

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 in a mammogram.

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. Pooled miss rates for polyps are as high as 22%, ...

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 animal models. This study aims to determine the imm...

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 reservoir, specifically the creation and stabilit...

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 and precisely how they alter or enhance vaccine-ind...

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 prediction is a major challenge in drug discovery. We...

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 automated biochemical and cell-based assays era. Th...

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- learning-based algorithm that uses basic patient infor...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from t...

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 better understand, disseminate, and incentivize hig...

Human-machine collaboration: bringing artificial intelligence into colonoscopy.

Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate ...

Transforming Diabetes Care Through Artificial Intelligence: The Future Is Here.

An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and yet 1 in 2 persons remain undiagnos...

Chemical Sensing at the Robot Fingertips: Toward Automated Taste Discrimination in Food Samples.

The development of robotic sensors that mimic the human sensing capabilities is critical for the interaction and cognitive abilities of modern robots....

Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished...

Estimation of the Basic Reproduction Number and Vaccination Coverage of Influenza in the United States (2017-18).

BACKGROUND: Determining the epidemic threshold parameter helps health providers calculate the coverage while guiding them in planning the process of v...

An accessible and efficient autism screening method for behavioural data and predictive analyses.

Autism spectrum disorder is associated with significant healthcare costs, and early diagnosis can substantially reduce these. Unfortunately, waiting t...