AIMC Topic: Humans

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Mandibular condyle detection using deep learning and double attractor-based energy valley optimizer algorithm.

BMC oral health
The temporomandibular joint (TMJ) constitutes a bilateral ginglymoarthrodial joint, wherein each condyle interacts with its corresponding glenoid fossa of the temporal bone. There is a critical need to understand better and accurately characterize th...

Integrated network toxicology, machine learning and molecular docking reveal the mechanism of benzopyrene-induced periodontitis.

BMC pharmacology & toxicology
BACKGROUND: Environmental pollutants, particularly from air pollution and tobacco smoke, have emerged as significant risk factors. Benzopyrene (BaP), a Group 1 carcinogen, is ubiquitously present in these pollutants, yet its molecular mechanisms in p...

AI for mental health: clinician expectations and priorities in computational psychiatry.

BMC psychiatry
Mental disorders represent a major global health challenge, with an estimated lifetime prevalence approaching 30%. Despite the availability of effective treatments, access to mental health care remains inadequate. Computational psychiatry, leveraging...

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

BMC oral health
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Scientific reports
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...

Inconsistency of AI in intracranial aneurysm detection with varying dose and image reconstruction.

Scientific reports
Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. In this study, we performed standardized consistency testing of an FDA-cleared and CE-marked AI for t...

Modeling eye gaze velocity trajectories using GANs with spectral loss for enhanced fidelity.

Scientific reports
Accurate modeling of eye gaze dynamics is essential for advancement in human-computer interaction, neurological diagnostics, and cognitive research. Traditional generative models like Markov models often fail to capture the complex temporal dependenc...

The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.

Scientific reports
To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics models for non-massive breast cancer in dense breast backgrounds. Manual segmentation of ultrasound image...

UANV: UNet-based attention network for thoracolumbar vertebral compression fracture angle measurement.

Scientific reports
Kyphosis is a prevalent spinal condition where the spine curves in the sagittal plane, resulting in spine deformities. Curvature estimation provides a powerful index to assess the deformation severity of scoliosis. In current clinical diagnosis, the ...

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome.

Scientific reports
Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients' quality of life, primarily due to impaired motor function and gait instability. Although conventional neurol...