AIMC Topic: Algorithms

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Wearable EEG Neurofeedback Based-on Machine Learning Algorithms for Children with Autism: A Randomized, Placebo-controlled Study.

Current medical science
OBJECTIVE: Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism spectrum disorder (ASD), while studies have also demonstrated that mirror neuron mu rhythm-based EE...

A Near-Infrared Imaging System for Robotic Venous Blood Collection.

Sensors (Basel, Switzerland)
Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. The success of this robotic approach is heavily d...

Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements.

Sensors (Basel, Switzerland)
The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may c...

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Scientific reports
Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with poor survival rates and quality of life, making the timely identification of high-risk patients for BMs in ES-SCLC crucial. Patients diagnosed with E...

A continuous pursuit dataset for online deep learning-based EEG brain-computer interface.

Scientific data
This dataset is from an EEG brain-computer interface (BCI) study investigating the use of deep learning (DL) for online continuous pursuit (CP) BCI. In this task, subjects use Motor Imagery (MI) to control a cursor to follow a randomly moving target,...

Automatic detection and proximity quantification of inferior alveolar nerve and mandibular third molar on cone-beam computed tomography.

Clinical oral investigations
OBJECTIVES: During mandibular third molar (MTM) extraction surgery, preoperative analysis to quantify the proximity of the MTM to the surrounding inferior alveolar nerve (IAN) is essential to minimize the risk of IAN injury. This study aims to propos...

An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).

A systematic review on feature extraction methods and deep learning models for detection of cancerous lung nodules at an early stage -the recent trends and challenges.

Biomedical physics & engineering express
Lung cancer is one of the most common life-threatening worldwide cancers affecting both the male and the female populations. The appearance of nodules in the scan image is an early indication of the development of cancer cells in the lung. The Low Do...

An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images.

Journal of advanced research
INTRODUCTION: Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for ...

Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.

The Journal of the American Academy of Orthopaedic Surgeons
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study was to determine the reliability of assessing surgical risk after hip fracture through machine learnin...