AIMC Topic: Female

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On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review.

Frontiers in public health
A significant challenge for hospitals and medical practitioners in low- and middle-income nations is the lack of sufficient health care facilities for timely medical diagnosis of chronic and deadly diseases. Particularly, maternal and neonatal morbid...

Unsupervised clustering of patients with severe aortic stenosis: A myocardial continuum.

Archives of cardiovascular diseases
BACKGROUND: Traditional statistics, based on prediction models with a limited number of prespecified variables, are probably not adequate to provide an appropriate classification of a condition that is as heterogeneous as aortic stenosis (AS).

Accurate detection of dairy cow mastitis with deep learning technology: a new and comprehensive detection method based on infrared thermal images.

Animal : an international journal of animal bioscience
Mastitis is one of the most common diseases in dairy cows and has a negative impact on their welfare and life, causing significant economic losses to the dairy industry. Many attempts have been made to develop a detection method for mastitis using th...

Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization.

Sensors (Basel, Switzerland)
Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. In vitro fertilization (IVF) is one of those assisted reproduction methods in which the sperm and egg...

Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations.

International journal of molecular sciences
Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocar...

Estimation of Cerebral Blood Flow and Arterial Transit Time From Multi-Delay Arterial Spin Labeling MRI Using a Simulation-Based Supervised Deep Neural Network.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: An inherently poor signal-to-noise ratio (SNR) causes inaccuracy and less precision in cerebral blood flow (CBF) and arterial transit time (ATT) when using arterial spin labeling (ASL). Deep neural network (DNN)-based parameter estimation...

Robotic repair of a branching vesicouterine and vesicovaginal fistula.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: We present technical considerations and tips for repairing a complex branching vesicouterine and vesicovaginal fistula via a robotic approach.

Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism.

Tomography (Ann Arbor, Mich.)
Background: The accurate classification between malignant and benign breast lesions detected on mammograms is a crucial but difficult challenge for reducing false-positive recall rates and improving the efficacy of breast cancer screening. Objective:...

Improving breast cancer diagnostics with deep learning for MRI.

Science translational medicine
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast...

Generalizability and Bias in a Deep Learning Pediatric Bone Age Prediction Model Using Hand Radiographs.

Radiology
Background Although deep learning (DL) models have demonstrated expert-level ability for pediatric bone age prediction, they have shown poor generalizability and bias in other use cases. Purpose To quantify generalizability and bias in a bone age DL ...