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Explore the latest research on artificial intelligence and machine learning in medicine.

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Novel deep learning method for coronary artery tortuosity detection through coronary angiography.

Scientific reports
Coronary artery tortuosity is usually an undetected condition in patients undergoing coronary angiography. This condition requires a longer examination by the specialist to be detected. Yet, detailed knowledge of the morphology of coronary arteries i...

Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews.

Advances in therapy
INTRODUCTION: Several studies have emphasized the potential of artificial intelligence (AI) and its subfields, such as machine learning (ML), as emerging and feasible approaches to optimize patient care in oncology. As a result, clinicians and decisi...

Dataset dependency of low-density lipoprotein-cholesterol estimation by machine learning.

Annals of clinical biochemistry
OBJECTIVES: We evaluated the applicability of a machine learning-based low-density lipoprotein-cholesterol (LDL-C) estimation method and the influence of the characteristics of the training datasets.

Classification and Recognition of Building Appearance Based on Optimized Gradient-Boosted Decision Tree Algorithm.

Sensors (Basel, Switzerland)
There are high concentrations of urban spaces and increasingly complex land use types. Providing an efficient and scientific identification of building types has become a major challenge in urban architectural planning. This study used an optimized g...

A Convex Optimization Approach to Multi-Robot Task Allocation and Path Planning.

Sensors (Basel, Switzerland)
In real-world applications, multiple robots need to be dynamically deployed to their appropriate locations as teams while the distance cost between robots and goals is minimized, which is known to be an NP-hard problem. In this paper, a new framework...

Using machine learning to improve Q-matrix validation.

Behavior research methods
The Q-matrix, which specifies the relationship between items and attributes, is a crucial component of cognitive diagnostic models (CDMs). A precisely specified Q-matrix allows for valid cognitive diagnostic assessments. In practice, a Q-matrix is us...

Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol.

BMJ open
INTRODUCTION: Infectious keratitis (IK) represents the fifth-leading cause of blindness worldwide. A delay in diagnosis is often a major factor in progression to irreversible visual impairment and/or blindness from IK. The diagnostic challenge is fur...

Strengths and limitations of new artificial intelligence tool for rare disease epidemiology.

Journal of translational medicine
The recent paper by Kariampuzha et al. describes an exciting application of artificial intelligence to rare disease epidemiology. The authors' AI model appears to offer a major leap over Orphanet, the resource which is often a "first stop" for basic ...

Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design.

Journal of neuroengineering and rehabilitation
BACKGROUND: Machine-learning-based myocontrol of prosthetic devices suffers from a high rate of abandonment due to dissatisfaction with the training procedure and with the reliability of day-to-day control. Incremental myocontrol is a promising appro...

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

Scientific reports
The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional ap...