AIMC Topic: Humans

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Language models for biological research: a primer.

Nature methods
Language models are playing an increasingly important role in many areas of artificial intelligence (AI) and computational biology. In this primer, we discuss the ways in which language models, both those based on natural language and those based on ...

Applying interpretable machine learning in computational biology-pitfalls, recommendations and opportunities for new developments.

Nature methods
Recent advances in machine learning have enabled the development of next-generation predictive models for complex computational biology problems, thereby spurring the use of interpretable machine learning (IML) to unveil biological insights. However,...

A comprehensive overview of barriers and strategies for AI implementation in healthcare: Mixed-method design.

PloS one
Implementation of artificial intelligence systems for healthcare is challenging. Understanding the barriers and implementation strategies can impact their adoption and allows for better anticipation and planning. This study's objective was to create ...

MCAS-GP: Deep Learning-Empowered Middle Cerebral Artery Segmentation and Gate Proposition.

IEEE/ACM transactions on computational biology and bioinformatics
With the fast development of AI technologies, deep learning is widely applied for biomedical data analytics and digital healthcare. However, there remain gaps between AI-aided diagnosis and real-world healthcare demands. For example, hemodynamic para...

CMM: A CNN-MLP Model for COVID-19 Lesion Segmentation and Severity Grading.

IEEE/ACM transactions on computational biology and bioinformatics
In this paper, a CNN-MLP model (CMM) is proposed for COVID-19 lesion segmentation and severity grading in CT images. The CMM starts by lung segmentation using UNet, and then segmenting the lesion from the lung region using a multi-scale deep supervis...

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer.

IEEE/ACM transactions on computational biology and bioinformatics
Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attention. The most prevalent method for an early check is ultrasound examination. Traditional research mainly concentrates on promoting the performance of ...

A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elderly groups. Today, clinical diagnosis is the main diagnostic method of Parkinson's disease, but the diagnosis results are not ideal, especially in the ...

Morphological Rule-Constrained Object Detection of Key Structures in Infant Fundus Image.

IEEE/ACM transactions on computational biology and bioinformatics
The detection of optic disc and macula is an essential step for ROP (Retinopathy of prematurity) zone segmentation and disease diagnosis. This paper aims to enhance deep learning-based object detection with domain-specific morphological rules. Based ...

Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images.

IEEE/ACM transactions on computational biology and bioinformatics
Vessel border detection in IVUS images is essential for coronary disease diagnosis. It helps to obtain the clinical indices on the inner vessel morphology to indicate the stenosis. However, the existing methods suffer the challenge of scale-dependent...

A Secure High-Order Gene Interaction Detection Algorithm Based on Deep Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order ge...