AIMC Topic: Humans

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Artificial Intelligence in Surgical Research: Accomplishments and Future Directions.

American journal of surgery
MINI-ABSTRACT: The study introduces various methods of performing conventional ML and their implementation in surgical areas, and the need to move beyond these traditional approaches given the advent of big data.

Dental Caries Detection and Classification in CBCT Images Using Deep Learning.

International dental journal
OBJECTIVES: This study aimed to investigate the accuracy of deep learning algorithms to diagnose tooth caries and classify the extension and location of dental caries in cone beam computed tomography (CBCT) images. To the best of our knowledge, this ...

A Preliminary Investigation into Search and Matching for Tumor Discrimination in World Health Organization Breast Taxonomy Using Deep Networks.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Breast cancer is one of the most common cancers affecting women worldwide. It includes a group of malignant neoplasms with a variety of biological, clinical, and histopathologic characteristics. There are more than 35 different histologic forms of br...

Examining ChatGPT Performance on USMLE Sample Items and Implications for Assessment.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: In late 2022 and early 2023, reports that ChatGPT could pass the United States Medical Licensing Examination (USMLE) generated considerable excitement, and media response suggested ChatGPT has credible medical knowledge. This report analyzes...

Laparoscopic versus robotic TAPP/TEP inguinal hernia repair: a multicenter, propensity score weighted study.

Hernia : the journal of hernias and abdominal wall surgery
PURPOSE: The objective of this retrospective study was to assess safety and comparative clinical effectiveness of laparoscopic inguinal hernia repair (LIHR) and robot-assisted inguinal hernia repair (RIHR) from multi-institutional experience in Taiwa...

A cluster-based ensemble approach for congenital heart disease prediction.

Computer methods and programs in biomedicine
BACKGROUND: One of the most prevalent birth disorders is congenital heart diseases (CHD). Although CHD risk factors have been the subject of numerous studies, their propensity to cause CHD has not been tested. Particularly few research has attempted ...

Prompt tuning for parameter-efficient medical image segmentation.

Medical image analysis
Neural networks pre-trained on a self-supervision scheme have become the standard when operating in data rich environments with scarce annotations. As such, fine-tuning a model to a downstream task in a parameter-efficient but effective way, e.g. for...

A survey on cancer detection via convolutional neural networks: Current challenges and future directions.

Neural networks : the official journal of the International Neural Network Society
Cancer is a condition in which abnormal cells uncontrollably split and damage the body tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical images play an indispensable role in detecting various cancers; however,...