AIMC Topic: Humans

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Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

PloS one
BACKGROUND: Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously ...

New Technique for Introducing a Surgical Stapler during Robot-Assisted Lobectomy for Lung Cancer.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: The da Vinci Si version robot lacks a vascular stapler that can be controlled by the operating surgeon at the surgical console when dividing pulmonary vessels. Therefore, to initiate and safely perform robotic anatomical lobectomy for lun...

Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology.

The Canadian journal of cardiology
Many clinicians remain wary of machine learning because of longstanding concerns about "black box" models. "Black box" is shorthand for models that are sufficiently complex that they are not straightforwardly interpretable to humans. Lack of interpre...

Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research
AI relates broadly to the science of developing computer systems to imitate human intelligence, thus allowing for the automation of tasks that would otherwise necessitate human cognition. Such technology has increasingly demonstrated capacity to outp...

An [18F]FDG-PET/CT deep learning method for fully automated detection of pathological mediastinal lymph nodes in lung cancer patients.

European journal of nuclear medicine and molecular imaging
PURPOSE: The identification of pathological mediastinal lymph nodes is an important step in the staging of lung cancer, with the presence of metastases significantly affecting survival rates. Nodes are currently identified by a physician, but this pr...

Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Intraoperative detection of the marginal tissues is the last and most important step to complete the resection of adenocarcinoma and squamous cell carcinoma. However, the current intraoperative diagnosis is time-consuming and requires numerous steps ...

Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review.

Veterinary pathology
Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. Whil...

Automated claustrum segmentation in human brain MRI using deep learning.

Human brain mapping
In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in vivo studies of the claustrum exist in humans. A reason for this may ...

Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.

Orthodontics & craniofacial research
Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning underlying biomedicine. Complexity theory, Network analysis and Artificial Intelligence are already appro...