AIMC Topic: Female

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Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.

AJR. American journal of roentgenology
Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily evaluated at tertiary and/or urban medical centers by radiologists with breast ultrasound expertise. The purpose of this study was to evaluate the usefu...

Artificial intelligence for sperm selection-a systematic review.

Fertility and sterility
Despite the increasing number of assisted reproductive technologies based treatments being performed worldwide, there has been little improvement in fertilization and pregnancy outcomes. Male infertility is a major contributing factor, and sperm eval...

Smart IoT in Breast Cancer Detection Using Optimal Deep Learning.

Journal of digital imaging
IoT in healthcare systems is currently a viable option for providing higher-quality medical care for contemporary e-healthcare. Using an Internet of Things (IoT)-based smart healthcare system, a trustworthy breast cancer classification method called ...

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Radiology
Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independe...

Discovery of novel PARP-1 inhibitors using tandem studies: integrated docking, e-pharmacophore, deep learning based de novo and molecular dynamics simulation approach.

Journal of biomolecular structure & dynamics
Cancer accounts for the majority of deaths worldwide, and the increasing incidence of breast cancer is a matter of grave concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as an attractive target for the treatment of breast cancer as it has...

Deep learning-based classification of breast lesions using dynamic ultrasound video.

European journal of radiology
PURPOSE: We intended to develop a deep-learning-based classification model based on breast ultrasound dynamic video, then evaluate its diagnostic performance in comparison with the classic model based on ultrasound static image and that of different ...

Society for birth defects research and prevention's multidisciplinary research needs workshop 2022: A call to action.

Birth defects research
The Society for Birth Defects Research and Prevention (BDRP) strives to understand and protect against potential hazards to developing embryos, fetuses, children, and adults by bringing together scientific knowledge from diverse fields. The theme of ...

Research Participant Selection Bias in the Workshop Using Socially Assistive Robots for Older Adults and Its Effect on Population Representativeness.

International journal of environmental research and public health
Every research participant has their own personality characteristics. For example, older adults assisted by socially assistive robots (SAR) may have their own unique characteristics and may not be representative of the general population of older adu...

Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classified.

PloS one
Differentiating the intrinsic subtypes of breast cancer is crucial for deciding the best treatment strategy. Deep learning can predict the subtypes from genetic information more accurately than conventional statistical methods, but to date, deep lear...

Classification of breast tumors by using a novel approach based on deep learning methods and feature selection.

Breast cancer research and treatment
PURPOSE: Cancer is one of the most insidious diseases that the most important factor in overcoming the cancer is early diagnosis and detection. The histo-pathological images are used to determine whether the tissue is cancerous and the type of cancer...