AIMC Topic: Humans

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A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet+.

BMC cancer
OBJECTIVE: Radiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tumor are gradually increasing. Manual segmentation of normal hepatic tissue and tumor exhibits limitations.

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

Scientific reports
This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its ...

Humor appreciation can be predicted with machine learning techniques.

Scientific reports
Humor research is supposed to predict whether something is funny. According to its theories and observations, amusement should be predictable based on a wide variety of variables. We test the practical value of humor appreciation research in terms of...

How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.

Scientific reports
Over the past decade, the use of deep learning has been widely increasing in the medical image diagnosis field. Deep learning-based methods' (DLMs) performance strongly relies on training data. Therefore, researchers often focus on collecting as much...

Determining body height and weight from thoracic and abdominal CT localizers in pediatric and young adult patients using deep learning.

Scientific reports
In this retrospective study, we aimed to predict the body height and weight of pediatric patients using CT localizers, which are overview scans performed before the acquisition of the CT. We trained three commonly used networks (EfficientNetV2-S, Res...

Fetal biometry and amniotic fluid volume assessment end-to-end automation using Deep Learning.

Nature communications
Fetal biometry and amniotic fluid volume assessments are two essential yet repetitive tasks in fetal ultrasound screening scans, aiding in the detection of potentially life-threatening conditions. However, these assessment methods can occasionally yi...

identifies gender disparities in scientific peer review.

eLife
The peer review process is a critical step in ensuring the quality of scientific research. However, its subjectivity has raised concerns. To investigate this issue, I examined over 500 publicly available peer review reports from 200 published neurosc...

Impact of Visceral Fat Area on Intraoperative Complexity and Surgical Approach Decision for Robot-Assisted Partial Nephrectomy: A Comparative Analysis with BMI.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Optimizing surgical approaches for robot-assisted partial nephrectomy (RAPN) is vital for better patient outcomes. This retrospective study aimed to examine how visceral fat area (VFA) and body mass index (BMI) correlate with intraoperativ...

Commercial artificial intelligence lateral cephalometric analysis: part 2-effects of human examiners on artificial intelligence performance, a pilot study.

The Journal of clinical pediatric dentistry
At the current technology level, a human examiner's review must be accompanied to compensate for the insufficient commercial artificial intelligence (AI) performance. This study aimed to investigate the effects of the human examiner's expertise on th...

Commercial artificial intelligence lateral cephalometric analysis: part 1-the possibility of replacing manual landmarking with artificial intelligence service.

The Journal of clinical pediatric dentistry
Artificial intelligence (AI) technology has recently been introduced to dentistry. AI-assisted cephalometric analysis is one of its applications, and several commercial AI services have already been launched. However, the performance of these commerc...