AIMC Topic: Deep Learning

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Cow key point detection in indoor housing conditions with a deep learning model.

Journal of dairy science
Lameness in dairy cattle is a costly and highly prevalent problem that affects all aspects of sustainable dairy production, including animal welfare. Automation of gait assessment would allow monitoring of locomotion in which the cows' walking patter...

Deep learning for diagnosis of head and neck cancers through radiographic data: a systematic review and meta-analysis.

Oral radiology
PURPOSE: This study aims to review deep learning applications for detecting head and neck cancer (HNC) using magnetic resonance imaging (MRI) and radiographic data.

GeneSegNet: a deep learning framework for cell segmentation by integrating gene expression and imaging.

Genome biology
When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We developed a dee...

Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals.

BMC medical informatics and decision making
BACKGROUND: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and monitor cardiac arrhythmia n...

Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning.

BMC medical imaging
BACKGROUND: The deterministic deep learning models have achieved state-of-the-art performance in various medical image analysis tasks, including nuclei segmentation from histopathology images. The deterministic models focus on improving the model pre...

White blood cell image analysis for infection detection based on virtual hexagonal trellis (VHT) by using deep learning.

Scientific reports
White blood cells (WBCs) are an indispensable constituent of the immune system. Efficient and accurate categorization of WBC is a critical task for disease diagnosis by medical experts. This categorization helps in the correct identification of medic...

Rapid prediction of lab-grown tissue properties using deep learning.

Physical biology
The interactions between cells and the extracellular matrix are vital for the self-organisation of tissues. In this paper we present proof-of-concept to use machine learning tools to predict the role of this mechanobiology in the self-organisation of...

Taylor Remora optimization enabled deep learning algorithms for percentage of pesticide detection in grapes.

Environmental science and pollution research international
In the world, grapes are considered as the most significant fruit, and it comprises various nutrients, like Vitamin C and it is utilized to produce wines and raisins. The major six general grape leaf diseases and pests are brown spots, leaf blight, d...

Deep learning-based identification of spine growth potential on EOS radiographs.

European radiology
OBJECTIVES: To develop an automatic computer-based method that can help clinicians in assessing spine growth potential based on EOS radiographs.

Deep Learning Model Based on Multisequence MRI Images for Assessing Adverse Pregnancy Outcome in Placenta Accreta.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Preoperative assessment of adverse outcomes risk in placenta accreta spectrum (PAS) disorders is of high clinical relevance for perioperative management and prognosis.