AIMC Topic: Algorithms

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Citation screening using crowdsourcing and machine learning produced accurate results: Evaluation of Cochrane's modified Screen4Me service.

Journal of clinical epidemiology
OBJECTIVES: To assess the feasibility of a modified workflow that uses machine learning and crowdsourcing to identify studies for potential inclusion in a systematic review.

Difficulty-aware hierarchical convolutional neural networks for deformable registration of brain MR images.

Medical image analysis
The aim of deformable brain image registration is to align anatomical structures, which can potentially vary with large and complex deformations. Anatomical structures vary in size and shape, requiring the registration algorithm to estimate deformati...

Can machine learning be useful as a screening tool for depression in primary care?

Journal of psychiatric research
Depression is a widespread disease with a high economic burden and a complex pathophysiology disease that is still not wholly clarified, not to mention it usually is associated as a risk factor for absenteeism at work and suicide. Just 50% of patient...

IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) are at the focus of attention due to their therapeutic importance and developing computational tools for the identification of efficient antibiotics from the primary structure. Here, we utilized the CNMR spectral of amin...

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks.

PLoS computational biology
A basic-yet nontrivial-function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Stable neocortical activity is asynchronous, critical, and low rate, and these features of spiking dynamics contrib...

Accelerating T mapping of the brain by integrating deep learning priors with low-rank and sparse modeling.

Magnetic resonance in medicine
PURPOSE: To accelerate T mapping with highly sparse sampling by integrating deep learning image priors with low-rank and sparse modeling.

The application of deep learning for the classification of correct and incorrect SNP genotypes from whole-genome DNA sequencing pipelines.

Journal of applied genetics
A downside of next-generation sequencing technology is the high technical error rate. We built a tool, which uses array-based genotype information to classify next-generation sequencing-based SNPs into the correct and the incorrect calls. The deep le...

An entropy-based approach to detect and localize intraoperative bleeding during minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: During minimally invasive surgery (either robotic or traditional laparoscopic), vascular injuries may occur because of inadvertent surgical tool movements or actions. These vascular injuries can lead to arterial or venous bleeding with va...

Prognostic machine learning models for COVID-19 to facilitate decision making.

International journal of clinical practice
An increasing number of COVID-19 cases worldwide has overwhelmed the healthcare system. Physicians are struggling to allocate resources and to focus their attention on high-risk patients, partly because early identification of high-risk individuals i...

AI in the treatment of fertility: key considerations.

Journal of assisted reproduction and genetics
Artificial intelligence (AI) has been proposed as a potential tool to help address many of the existing problems related with empirical or subjective assessments of clinical and embryological decision points during the treatment of infertility. AI te...