AIMC Topic: Female

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Computer-aided diagnosis of pectus excavatum using CT images and deep learning methods.

Scientific reports
Pectus excavatum (PE) is one of the most common chest wall defects. Accurate assessment of PE deformities is critical for effective surgical intervention. Index-based evaluations have become the standard for objectively estimating PE, however, these ...

Machine learning to predict early TNF inhibitor users in patients with ankylosing spondylitis.

Scientific reports
We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in patients with ankylosing spondylitis. The baseline demographic and laboratory data of patients who visited Samsung Medical Center rheumatology clinic ...

Learning to segment images with classification labels.

Medical image analysis
Two of the most common tasks in medical imaging are classification and segmentation. Either task requires labeled data annotated by experts, which is scarce and expensive to collect. Annotating data for segmentation is generally considered to be more...

The image quality of deep-learning image reconstruction of chest CT images on a mediastinal window setting.

Clinical radiology
AIM: To assess the image quality of deep-learning image reconstruction (DLIR) of chest computed tomography (CT) images on a mediastinal window setting in comparison to an adaptive statistical iterative reconstruction (ASiR-V).

Using machine learning-based analytics of daily activities to identify modifiable risk factors for falling in Parkinson's disease.

Parkinsonism & related disorders
BACKGROUND: Although risk factors that lead to falling in Parkinson's disease (PD) have been previously studied, the established predictors are mostly non-modifiable. A novel method for fall risk assessment may provide more insight into preventable h...

Automated estimation of echocardiogram image quality in hospitalized patients.

The international journal of cardiovascular imaging
We developed a machine learning model for efficient analysis of echocardiographic image quality in hospitalized patients. This study applied a machine learning model for automated transthoracic echo (TTE) image quality scoring in three inpatient grou...

Visual Guidance and Egg Collection Scheme for a Smart Poultry Robot for Free-Range Farms.

Sensors (Basel, Switzerland)
Free-range chicken farming allows egg-laying hens to move freely through their environment and perform their natural behavior, including laying her eggs. However, it takes time to gather these eggs manually, giving rise to high labor costs. This stud...

Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes.

BMC medical informatics and decision making
BACKGROUND: Accurately predicting patient outcomes in Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could aid patient management and allocation of healthcare resources. There are a variety of methods which can be used to develop progno...

Quantitative Methods for Analyzing Intimate Partner Violence in Microblogs: Observational Study.

Journal of medical Internet research
BACKGROUND: Social media is a rich, virtually untapped source of data on the dynamics of intimate partner violence, one that is both global in scale and intimate in detail.

Perspectives of Child Life Specialists After Many Years of Working With a Humanoid Robot in a Pediatric Hospital: Narrative Design.

Journal of medical Internet research
BACKGROUND: Child life specialists (CLSs) play an important role in supporting patients and their families during their visits to a children's hospital. Although CLSs are equipped with considerable expertise to support families during some of the mos...