AIMC Topic: Machine Learning

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Predicting sensory evaluation of spinach freshness using machine learning model and digital images.

PloS one
The visual perception of freshness is an important factor considered by consumers in the purchase of fruits and vegetables. However, panel testing when evaluating food products is time consuming and expensive. Herein, the ability of an image processi...

Artificial Intelligence, Machine Learning, and Surgical Science: Reality Versus Hype.

The Journal of surgical research
Artificial intelligence (AI) has made increasing inroads in clinical medicine. In surgery, machine learning-based algorithms are being studied for use as decision aids in risk prediction and even for intraoperative applications, including image recog...

Predicting Readmission After Anterior, Posterior, and Posterior Interbody Lumbar Spinal Fusion: A Neural Network Machine Learning Approach.

World neurosurgery
BACKGROUND: Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the conclusions remain equivocal. Machine learning algorithms offer a unique perspec...

Artificial Intelligence (AI) and Retinal Optical Coherence Tomography (OCT).

Seminars in ophthalmology
Ophthalmology has been at the forefront of medical specialties adopting artificial intelligence. This is primarily due to the "image-centric" nature of the field. Thanks to the abundance of patients' OCT scans, analysis of OCT imaging has greatly ben...

Preoperative prediction of regional lymph node metastasis of colorectal cancer based on F-FDG PET/CT and machine learning.

Annals of nuclear medicine
PURPOSE: To establish and validate a regional lymph node (LN) metastasis prediction model of colorectal cancer (CRC) based on F-FDG PET/CT and radiomic features using machine-learning methods.

Hybrid artificial fish particle swarm optimizer and kernel extreme learning machine for type-II diabetes predictive model.

Medical & biological engineering & computing
The World Health Organization (WHO) estimated that in 2016, 1.6 million deaths caused were due to diabetes. Precise and on-time diagnosis of type-II diabetes is crucial to reduce the risk of various diseases such as heart disease, stroke, kidney dise...

Transfer learning-based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan data.

Medical & biological engineering & computing
The novel discovered disease coronavirus popularly known as COVID-19 is caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and declared a pandemic by the World Health Organization (WHO). An early-stage detection of COVID-19 is...

Comparison of machine learning methods for prediction of osteoradionecrosis incidence in patients with head and neck cancer.

The British journal of radiology
OBJECTIVES: Mandible osteoradionecrosis (ORN) is one of the most severe toxicities in patients with head and neck cancer (HNC) undergoing radiotherapy (RT). The existing literature focuses on the correlation of mandible ORN and clinical and dosimetri...

Evaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning.

IEEE transactions on bio-medical engineering
Evaluating progress throughout a patient's rehabilitation episode is critical for determining the effectiveness of the selected treatments and is an essential ingredient in personalised and evidence-based rehabilitation practice. The evaluation proce...

Machine learning to determine optimal conditions for controlling the size of elastin-based particles.

Scientific reports
This paper evaluates the aggregation behavior of a potential drug and gene delivery system that combines branched polyethyleneimine (PEI), a positively-charged polyelectrolyte, and elastin-like polypeptide (ELP), a recombinant polymer that exhibits l...