AIMC Topic: Humans

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Harnessing artificial intelligence in the post-COVID-19 era: A global health imperative.

Tropical doctor
Despite the World Health Organization's declaration that the COVID-19 global emergency has ended, the threat of future pandemics remains a significant concern. This paper highlights the potential role of Artificial Intelligence (AI) in strengthening ...

Robot-assisted laparoscopic abdominoperineal resection for anal canal cancer associated with Crohn's disease: A case report.

Asian journal of endoscopic surgery
A 37-year-old man with Crohn's disease (CD) and a history of abdominal surgery was diagnosed with anal canal cancer. Robot-assisted laparoscopic abdominoperineal resection was performed and the patient was discharged without any postoperative complic...

Robotic-Assisted Transabdominal Inferior Retroperitoneal Approach: an Alternative to Cattell-Braash Maneuver.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
INTRODUCTION: The Cattell-Braasch maneuver has been widely used to provide adequate exposure for aorto-caval space (ACS) since the 1960s. Given its requirement of complex visceral mobilization and significant physiological disturbance, we proposed a ...

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations.

Computers in biology and medicine
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detect...

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

European radiology
OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.

An open competition involving thousands of competitors failed to construct useful abstract classifiers for new diagnostic test accuracy systematic reviews.

Research synthesis methods
There are currently no abstract classifiers, which can be used for new diagnostic test accuracy (DTA) systematic reviews to select primary DTA study abstracts from database searches. Our goal was to develop machine-learning-based abstract classifiers...