AIMC Topic: Young Adult

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A pilot study of machine-learning based automated planning for primary brain tumours.

Radiation oncology (London, England) Jan 6, 2022
PURPOSE: High-quality radiotherapy (RT) planning for children and young adults with primary brain tumours is essential to minimize the risk of late treatment effects. The feasibility of using automated machine-learning (ML) to aid RT planning in this...
Humans Machine Learning Middle Aged Pilot Projects Adolescent Child, Preschool Child Radiotherapy Planning, Computer-Assisted Female Aged Young Adult Adult Brain Neoplasms Male
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Predicting speech discrimination scores from pure-tone thresholds-A machine learning-based approach using data from 12,697 subjects.

PloS one Dec 31, 2021
Diagnostic tests for hearing impairment not only determines the presence (or absence) of hearing loss, but also evaluates its degree and type, and provides physicians with essential data for future treatment and rehabilitation. Therefore, accurately ...
Hearing Loss Speech Perception Auditory Threshold Adult Discrimination Learning Female Humans Male Speech Reception Threshold Test Infant, Newborn Neural Networks, Computer Middle Aged Reproducibility of Results Child, Preschool Machine Learning Infant Aged Child Adolescent Aged, 80 and over Algorithms Computational Biology Young Adult Republic of Korea Models, Statistical Audiometry, Pure-Tone Hearing
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Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Circulation. Heart failure Dec 24, 2021
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...
Humans Machine Learning Prospective Studies Cohort Studies Young Adult Myocardium Adult Registries Middle Aged Heart Ventricles Adolescent Heart Failure Incidence Heart-Assist Devices
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Perceptions of the use of artificial intelligence in the diagnosis of skin cancer: an outpatient survey.

Clinical and experimental dermatology Dec 23, 2021
BACKGROUND: Convolutional neural networks (artificial intelligence, AI) are rapidly appearing within the field of dermatology, with diagnostic accuracy matching that of dermatologists. As technologies become available for use by both the health profe...
Health Surveys Age Factors Patient Acceptance of Health Care Attitude to Health Female Humans Cross-Sectional Studies Skin Neoplasms Male Artificial Intelligence Middle Aged Aged Diagnosis, Computer-Assisted Aged, 80 and over Adolescent Young Adult Adult
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Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.

PloS one Dec 23, 2021
BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysi...
Humans Corpus Callosum Female Aged Young Adult Adult Cross-Sectional Studies Adolescent Male Cognitive Dysfunction Middle Aged Child Risk Assessment Magnetic Resonance Imaging Disease Progression Alzheimer Disease Case-Control Studies Atrophy Deep Learning
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Weakly-supervised deep learning for ultrasound diagnosis of breast cancer.

Scientific reports Dec 21, 2021
Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We aimed to develop a weakly-supervised DL algorithm that diagnosis breast cancer at ultrasound without...
Diagnosis, Differential Ultrasonography, Mammary Breast Image Interpretation, Computer-Assisted Humans Case-Control Studies Neural Networks, Computer Deep Learning Aged Algorithms Adolescent Prognosis Aged, 80 and over ROC Curve Retrospective Studies Young Adult Follow-Up Studies Female Adult Breast Neoplasms Middle Aged
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Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies.

Scientific reports Dec 20, 2021
Chronic exertional compartment syndrome (CECS) is a condition occurring most frequently in the lower limbs and often requires corrective surgery to alleviate symptoms. Amongst military personnel, the success rates of this surgery can be as low as 20%...
Area Under Curve Military Personnel Linear Models Leg Fasciotomy Return to Work ROC Curve Treatment Outcome Support Vector Machine Lower Extremity Models, Statistical Chronic Exertional Compartment Syndrome Prognosis Female Reproducibility of Results Young Adult Adult Humans Sensitivity and Specificity Machine Learning Male Middle Aged Exercise Surveys and Questionnaires Time Factors
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Computed tomography radiomics for the prediction of thymic epithelial tumor histology, TNM stage and myasthenia gravis.

PloS one Dec 20, 2021
OBJECTIVES: To evaluate CT-derived radiomics for machine learning-based classification of thymic epithelial tumor (TET) stage (TNM classification), histology (WHO classification) and the presence of myasthenia gravis (MG).
Male Middle Aged Follow-Up Studies Neoplasm Staging Neoplasms, Glandular and Epithelial Myasthenia Gravis Histological Techniques Thymus Neoplasms Tomography, X-Ray Computed Female Aged Aged, 80 and over Young Adult Adult Humans Machine Learning Algorithms Retrospective Studies
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Percutaneous Robot-Assisted versus Freehand S Iliosacral Screw Fixation in Unstable Posterior Pelvic Ring Fracture.

Orthopaedic surgery Dec 13, 2021
OBJECTIVES: To assess the efficiency, safety, and accuracy of S (IS) screw fixation using a robot-assisted method compared with a freehand method.
Male Middle Aged Pelvic Bones Fractures, Bone Fracture Fixation, Internal Robotics Humans Retrospective Studies Female Young Adult Adult Bone Screws
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Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations.

Nature medicine Dec 10, 2021
Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing concern that such AI systems may reflect and amplify human bias, and reduce the quality of their perfo...
Child, Preschool Child Infant, Newborn Humans Datasets as Topic Young Adult Artificial Intelligence Radiography, Thoracic Male Algorithms Infant Female Vulnerable Populations Adolescent
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