AIMC Topic: Female

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Assessment of artificial intelligence model and manual morphokinetic annotation system as embryo grading methods for successful live birth prediction: a retrospective monocentric study.

Reproductive biology and endocrinology : RB&E
PURPOSE: The introduction of the time-lapse monitoring system (TMS) and the development of predictive algorithms could contribute to the optimal embryos selection for transfer. Therefore, the present study aims at investigating the efficiency of KIDS...

A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI.

Scientific reports
Breast density, or the amount of fibroglandular tissue (FGT) relative to the overall breast volume, increases the risk of developing breast cancer. Although previous studies have utilized deep learning to assess breast density, the limited public ava...

What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT.

Journal of medical Internet research
BACKGROUND: Artificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and...

Teardrop Alignment Changes After Volar Locking Plate Fixation of Distal Radius Fractures With Volar Ulnar Fragments.

Hand (New York, N.Y.)
BACKGROUND: We assessed factors associated with change in radiographic teardrop angle following volar locking plate (VLP) fixation of volarly displaced intra-articular distal radius fractures with volar ulnar fragments (VUF) within the ICUC database....

More Is Not Always Better: Impacts of AI-Generated Confidence and Explanations in Human-Automation Interaction.

Human factors
OBJECTIVE: The study aimed to enhance transparency in autonomous systems by automatically generating and visualizing confidence and explanations and assessing their impacts on performance, trust, preference, and eye-tracking behaviors in human-automa...

Addressing the Contrast Media Recognition Challenge: A Fully Automated Machine Learning Approach for Predicting Contrast Phases in CT Imaging.

Investigative radiology
OBJECTIVES: Accurately acquiring and assigning different contrast-enhanced phases in computed tomography (CT) is relevant for clinicians and for artificial intelligence orchestration to select the most appropriate series for analysis. However, this i...

Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm.

Journal of imaging informatics in medicine
Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT)...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Journal of imaging informatics in medicine
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihyper...