AIMC Topic: Humans

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A VS ultrasound diagnostic system with kidney image evaluation functions.

International journal of computer assisted radiology and surgery
PURPOSE: An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of the physician operating the probe. This is because physicians have to constantly adjust the probe posi...

Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study.

European radiology
OBJECTIVES: To compare image quality between a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) and to assess the impact of these algorithms on radiomics robustness...

Deep-learning model associating lateral cervical radiographic features with Cormack-Lehane grade 3 or 4 glottic view.

Anaesthesia
Unanticipated difficult laryngoscopy is associated with serious airway-related complications. We aimed to develop and test a convolutional neural network-based deep-learning model that uses lateral cervical spine radiographs to predict Cormack-Lehane...

High-resolution knee plain radiography image synthesis using style generative adversarial network adaptive discriminator augmentation.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In this retrospective study, 10,000 anteroposterior (AP) radiography of the knee from a single institution was used to create medical data set that are more balanced and cheaper to create. Two types of convolutional networks were used, deep convoluti...

Evaluation of advanced curve speed warning system to prevent fire truck rollover crashes.

Journal of safety research
INTRODUCTION: A disproportionately high number of deadly crash-incidents involve fire-tanker rollovers during emergency response driving. Most of these rollover incidents occur at dangerous horizontal curves ("curves") due to unsafe speed. This study...

Robotic vs. laparoscopic intersphincteric resection for low rectal cancer: a case matched study reporting a median of 7-year long-term oncological and functional outcomes.

Updates in surgery
Aim of this study was to compare operative, long-term oncological and functional outcomes of laparoscopic (LISR) and robotic (RISR) intersphincteric resection in low-lying rectal cancer. Retrospective analysis of prospectively maintained database was...

Artificial intelligence-augmented histopathologic review using image analysis to optimize DNA yield from formalin-fixed paraffin-embedded slides.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
To achieve minimum DNA input requirements for next-generation sequencing (NGS), pathologists visually estimate macrodissection and slide count decisions. Unfortunately, misestimation may cause tissue waste and increased laboratory costs. We developed...

Interpretable deep learning-based hippocampal sclerosis classification.

Epilepsia open
OBJECTIVE: To evaluate the performance of a deep learning model for hippocampal sclerosis classification on the clinical dataset and suggest plausible visual interpretation for the model prediction.

Development and model form assessment of an automatic subject-specific vertebra reconstruction method.

Computers in biology and medicine
BACKGROUND: Current spine models for analog bench models, surgical navigation and training platforms are conventionally based on 3D models from anatomical human body polygon database or from time-consuming manual-labelled data. This work proposed a w...

Disentangled representation for sequential treatment effect estimation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Treatment effect estimation, as a fundamental problem in causal inference, focuses on estimating the outcome difference between different treatments. However, in clinical observational data, some patient covariates (such as ...