AIMC Topic: Female

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Deep Learning-Based Risk Model for Best Management of Closed Groin Incisions After Vascular Surgery.

The Journal of surgical research
BACKGROUND: Reduced surgical site infection (SSI) rates have been reported with use of closed incision negative pressure therapy (ciNPT) in high-risk patients.

Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.

Radiology
Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment planning, which is time consuming and potentially challenging. Purpose To develop and investigate deep learning (DL) methods for detecting brain meta...

A convolutional neural network-based system to classify patients using FDG PET/CT examinations.

BMC cancer
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...

Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data.

Journal of medical Internet research
BACKGROUND: Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morbidity and mortality, especially in the elderly. With a rapid growth of the elderly population in recent years, lung cancer prevention and control are ...

Novel body fat estimation using machine learning and 3-dimensional optical imaging.

European journal of clinical nutrition
Estimates of body composition have been derived using 3-dimensional optical imaging (3DO), but no equations to date have been calibrated using a 4-component (4C) model criterion. This investigation reports the development of a novel body fat predicti...

Machine Learning Diagnostic Modeling for Classifying Fibromyalgia Using B-mode Ultrasound Images.

Ultrasonic imaging
Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quantitative ultrasound (US) techniques, such as image texture analysis, which has demonstrated discrimina...

Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data.

Scientific reports
Cell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (ML) have been playing a pivotal role in revolutionizing medical diagnostics. This research presents ...

Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD.

NeuroImage. Clinical
BACKGROUND: Those with autism spectrum disorder (ASD) and/or attention-deficit-hyperactivity disorder (ADHD) exhibit symptoms of hyperactivity and inattention, causing significant hardships for families and society. A potential mechanism involved in ...

Attitudes of Patients and Their Relatives Toward Artificial Intelligence in Neurosurgery.

World neurosurgery
BACKGROUND: Artificial intelligence (AI) may favorably support surgeons but can result in concern among patients and their relatives. The aim of this study was to evaluate attitudes of patients and their relatives regarding use of AI in neurosurgery.

Challenge Accepted? Individual Performance Gains for Motor Imagery Practice with Humanoid Robotic EEG Neurofeedback.

Sensors (Basel, Switzerland)
Optimizing neurofeedback (NF) and brain-computer interface (BCI) implementations constitutes a challenge across many fields and has so far been addressed by, among others, advancing signal processing methods or predicting the user's control ability f...