AIMC Topic: Humans

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Identifying fetal status with fetal heart rate: Deep learning approach based on long convolution.

Computers in biology and medicine
CTG (Cardiotocography) is an effective tool for fetal status assessment. Clinically, doctors mainly evaluate the health of fetus by observing FHR (fetal heart rate). The rapid development of Artificial Intelligence has led realization of computer-aid...

Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.

The Lancet. Digital health
BACKGROUND: Retinopathy of prematurity (ROP), a leading cause of childhood blindness, is diagnosed through interval screening by paediatric ophthalmologists. However, improved survival of premature neonates coupled with a scarcity of available expert...

Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial.

The Lancet. Digital health
BACKGROUND: Pretreatment identification of pathological extranodal extension (ENE) would guide therapy de-escalation strategies for in human papillomavirus (HPV)-associated oropharyngeal carcinoma but is diagnostically challenging. ECOG-ACRIN Cancer ...

XAI-enabled neural network analysis of metabolite spatial distributions.

Analytical and bioanalytical chemistry
We used deep neural networks to process the mass spectrometry imaging (MSI) data of mouse muscle (young vs aged) and human cancer (tumor vs normal adjacent) tissues, with the aim of using explainable artificial intelligence (XAI) methods to rapidly i...

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping.

Journal of visualized experiments : JoVE
To grasp an object successfully, we must select appropriate contact regions for our hands on the surface of the object. However, identifying such regions is challenging. This paper describes a workflow to estimate the contact regions from marker-base...

A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian Detection.

Sensors (Basel, Switzerland)
Most pedestrian detection methods focus on bounding boxes based on fusing RGB with lidar. These methods do not relate to how the human eye perceives objects in the real world. Furthermore, lidar and vision can have difficulty detecting pedestrians in...

Design of a Convolutional Neural Network as a Deep Learning Tool for the Automatic Classification of Small-Bowel Cleansing in Capsule Endoscopy.

Medicina (Kaunas, Lithuania)
: Capsule endoscopy (CE) is a non-invasive method to inspect the small bowel that, like other enteroscopy methods, requires adequate small-bowel cleansing to obtain conclusive results. Artificial intelligence (AI) algorithms have been seen to offer i...

Predicting disease genes based on multi-head attention fusion.

BMC bioinformatics
BACKGROUND: The identification of disease-related genes is of great significance for the diagnosis and treatment of human disease. Most studies have focused on developing efficient and accurate computational methods to predict disease-causing genes. ...