AIMC Topic: Deep Learning

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TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile.

PLoS computational biology
Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in different biological conditions. Biological assays designed to directly mapping TFBSs require large sample s...

The effect of a deep-learning tool on dentists' performances in detecting apical radiolucencies on periapical radiographs.

Dento maxillo facial radiology
OBJECTIVES: To determine the efficacy of a deep-learning (DL) tool in assisting dentists in detecting apical radiolucencies on periapical radiographs.

Dance Action Recognition Model Using Deep Learning Network in Streaming Media Environment.

Journal of environmental and public health
Dance movement recognition is a video technology that has a significant impact on intelligent applications and is widely applied in many industries. In the training of intelligent dance assistants, this method can be used. Dancers' postures can be re...

Investigation of Applying Machine Learning and Hyperparameter Tuned Deep Learning Approaches for Arrhythmia Detection in ECG Images.

Computational and mathematical methods in medicine
The level of patient's illness is determined by diagnosing the problem through different methods like physically examining patients, lab test data, and history of patient and by experience. To treat the patient, proper diagnosis is very much importan...

Contribution of an artificial intelligence deep-learning reconstruction algorithm for dose optimization in lumbar spine CT examination: A phantom study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the impact of the new artificial intelligence deep-learning reconstruction (AI-DLR) algorithm on image quality and radiation dose compared with iterative reconstruction algorithm in lumbar spine comput...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Computers in biology and medicine
Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of ...

AntiMF: A deep learning framework for predicting anticancer peptides based on multi-view feature extraction.

Methods (San Diego, Calif.)
In recent years, anticancer peptides have emerged as a new viable option in cancer therapy, with the ability to overcome the considerable side effects and poor outcomes of standard cancer therapies. Accurate anticancer peptide identification can faci...

Assessment of deep learning pose estimates for sports collision tracking.

Journal of sports sciences
Injury assessment during sporting collisions requires estimation of the associated kinematics. While marker-based solutions are widely accepted as providing accurate and reliable measurements, setup times are lengthy and it is not always possible to ...

Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.

Computers in biology and medicine
OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...

Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Automated image-level detection of large vessel occlusions (LVO) could expedite patient triage for mechanical thrombectomy. A few studies have previously attempted LVO detection using artificial intelligence (AI) on CT angiography (CTA) i...