AIMC Topic: Reproducibility of Results

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Collision Cross Section Calculations to Aid Metabolite Annotation.

Journal of the American Society for Mass Spectrometry
The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low o...

Robot-assisted radical prostatectomy in the treatment of patients with clinically high-risk localized and locally advanced prostate cancer: single surgeons functional and oncologic outcomes.

BMC urology
BACKGROUND: Optimal treatment approaches for high-risk localized and locally advanced prostate cancer remain controversial and there are currently no standard treatments. These patients with high-risk localized and locally advanced prostate cancer ar...

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimation of various spinopelvic parameters. The locations of inflection points (IPs) and apices (APs) in ...

Using artificial intelligence to support rapid, mixed-methods analysis: Developing an automated qualitative assistant (AQUA).

Annals of family medicine
Context: Qualitative research - crucial for understanding human behavior - remains underutilized, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those bur...

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

NMR in biomedicine
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical...

Identification of Characteristic Points in Multivariate Physiological Signals by Sensor Fusion and Multi-Task Deep Networks.

Sensors (Basel, Switzerland)
Identification of characteristic points in physiological signals, such as the peak of the R wave in the electrocardiogram and the peak of the systolic wave of the photopletismogram, is a fundamental step for the quantification of clinical parameters,...

A framework for rigorous evaluation of human performance in human and machine learning comparison studies.

Scientific reports
Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, the...

Deep learning for caries detection: A systematic review.

Journal of dentistry
OBJECTIVES: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection.

Probing Diffusive Dynamics of Natural Tubule Nanoclays with Machine Learning.

ACS nano
Reproducibility of the experimental results and object of study itself is one of the basic principles in science. But what if the object characterized by technologically important properties is natural and cannot be artificially reproduced one-to-one...

Review of the Factors Affecting Acceptance of AI-Infused Systems.

Human factors
OBJECTIVE: The study aimed to provide a comprehensive overview of the factors impacting technology adoption, to predict the acceptance of artificial intelligence (AI)-based technologies.