AIMC Topic: Female

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Automated detection of fatal cerebral haemorrhage in postmortem CT data.

International journal of legal medicine
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progress...

Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.

Journal of imaging informatics in medicine
This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radiograph diagnosis. We adopted a deep learning algorithm to concurrently detect the presence of normal ...

Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens.

Virchows Archiv : an international journal of pathology
Crohn's disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristics, and differential diagnosis can be a dilemma for pathologists. This study aimed to apply deep learning (DL) to analyze whole slide images (WSI) of ...

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare, but pediatric critical care studies are scant. Our objective was to evaluate the utility of generative LMs in the pediatric critical care setting an...

Using deep neural networks to disentangle visual and semantic information in human perception and memory.

Nature human behaviour
Mental representations of familiar categories are composed of visual and semantic information. Disentangling the contributions of visual and semantic information in humans is challenging because they are intermixed in mental representations. Deep neu...

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images.

Computers in biology and medicine
Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus...

First clinical experiences of robotic gastrectomy for gastric cancer using the hinotori™ surgical robot system.

Surgical endoscopy
BACKGROUND: Although the da Vinci™ Surgical System is the most predominantly used surgical robot worldwide, other surgical robots are being developed. The Japanese surgical robot hinotori™ Surgical Robot System was launched and approved for clinical ...

Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity.

Techniques in coloproctology
BACKGROUND: Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity. Precision approach with robotic surgery leads to organ preservation. Bowel endometriosis requires a multidisciplinary m...

The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

AIDS and behavior
We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled National COVID Cohort Collaborative (N3C) data released from January 1, 2020 to October 10, 2022. We d...

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

Gastroenterology
BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous perfo...