AIMC Topic: Humans

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An investigation into the risk of population bias in deep learning autocontouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To date, data used in the development of Deep Learning-based automatic contouring (DLC) algorithms have been largely sourced from single geographic populations. This study aimed to evaluate the risk of population-based bias by...

Evaluating the Accuracy and Reliability of Blowout Fracture Area Measurement Methods: A Review and the Potential Role of Artificial Intelligence.

The Journal of craniofacial surgery
Blowout fractures are a common type of facial injury that requires accurate measurement of the fracture area for proper treatment planning. This systematic review aimed to summarize and evaluate the current methods for measuring blowout fracture area...

Collision avoidance analysis of human-robot physical interaction based on null-space impedance control of a dynamic reference arm plane.

Medical & biological engineering & computing
When the terminal upper limb rehabilitation robot is used for motion-assisted training, collisions between the manipulator links and the human upper limb may occur due to the null-space self-motion of the redundant manipulator. A null-space impedance...

An Optimized Deep Learning Model for Predicting Mild Cognitive Impairment Using Structural MRI.

Sensors (Basel, Switzerland)
Early diagnosis of mild cognitive impairment (MCI) with magnetic resonance imaging (MRI) has been shown to positively affect patients' lives. To save time and costs associated with clinical investigation, deep learning approaches have been used widel...

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images.

Scientific reports
Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridiza...

Detecting common coccinellids found in sorghum using deep learning models.

Scientific reports
Increased global production of sorghum has the potential to meet many of the demands of a growing human population. Developing automation technologies for field scouting is crucial for long-term and low-cost production. Since 2013, sugarcane aphid (S...

Genetic algorithm designed for optimization of neural network architectures for intracranial EEG recordings analysis.

Journal of neural engineering
The current practices of designing neural networks rely heavily on subjective judgment and heuristic steps, often dictated by the level of expertise possessed by architecture designers. To alleviate these challenges and streamline the design process,...

Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach.

Journal of neural engineering
. Hydrocephalus is the leading indication for pediatric neurosurgical care worldwide. Identification of postinfectious hydrocephalus (PIH) verses non-postinfectious hydrocephalus, as well as the pathogen involved in PIH is crucial for developing an a...

A narrative review of the mechanisms and consequences of intermittent hypoxia and the role of advanced analytic techniques in pediatric autonomic disorders.

Clinical autonomic research : official journal of the Clinical Autonomic Research Society
Disorders of autonomic functions are typically characterized by disturbances in multiple organ systems. These disturbances are often comorbidities of common and rare diseases, such as epilepsy, sleep apnea, Rett syndrome, congenital heart disease or ...