Computers in Biology and Medicine

Segmentation of clavicles and ribs in chest X-rays is significant for diagnosing lung diseases. However, it is challenging to segment ribs because of the low contrast on chest X-rays. Moreover, most existing methods fail to segment ...

• Segmentation of the chest X-ray plays a critical role in the computer-aided system.

Left ventricular ejection fraction (LVEF) is essential for evaluating left ventricular systolic function. However, its clinical calculation requires the physician to interactively segment the left ventricle and obtain the mitral ...

• A multi-task learning model is designed for both segmentation and landmark detection tasks.

Childhood Leukemia is the most common type of cancer among children. Nearly 39% of cancer-induced childhood deaths are attributable to Leukemia. Nevertheless, early intervention has long been underdeveloped. ...

• A robust Bayesian survival model for patient-specific survival probability predictions of childhood Leukemia.

Emotion recognition is a key component of human–computer interaction technology, for which facial electromyogram (fEMG) is an important physiological modality. Recently, deep-learning-based emotion recognition using fEMG signals has ...

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• Propose a spatio-temporal deep forest model to recognize emotions via fEMG signals.

Multimodal deep learning models have been applied for disease prediction tasks, but difficulties exist in training due to the conflict between sub-models and fusion modules. To alleviate this issue, we propose a framework for ...

• A novel multimodal deep learning framework is proposed.
• The framework solves ...

Mechanoelectric feedback (MEF) in the heart operates through several mechanisms which serve to regulate cardiac function. Stretch activated channels (SACs) in the myocyte membrane open in response to cell lengthening, while tension ...

• The role of mechanoelectric feedback mechanisms in the cardiac function is explored.

Accurate prediction of the trajectory of Alzheimer’s disease (AD) from an early stage is of substantial value for treatment and planning to delay the onset of AD. We propose a novel attention transfer method to train a 3D convolutional ...

• A novel attention transfer method for predicting MCI conversion to Alzheimer’s disease.

Left ventricular diastolic dyfunction detection is particularly important in cardiac function screening. This paper proposed a phonocardiogram (PCG) transfer learning-based CatBoost model to detect diastolic dysfunction noninvasively. ...

• Transfer learning can provide objective aid in diastolic dysfunction detection using phonocardiogram (PCG).

Coronavirus disease (COVID-19) has infected billion people around the world and affected the economy, but most countries are considering reopening, so the COVID-19 daily confirmed and death cases have increased greatly. It is very ...

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• Propose a novel prediction model for COVID-19 daily confirmed and death cases.
• ...

There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is an important cerebrovascular disease. Although deep learning-based models have been ...

• To the best of our knowledge, this is the first attempt at site generalization for stroke lesion segmentation.

Endovascular treatment of intracranial aneurysms with flow diverters (FD) has become one of the most promising interventions. Due to its woven high-density structure they are particularly applicable for challenging lesions. Although ...

• Pre- and post-interventional intracranial aneurysm models are considered for virtual flow diverter deployment.

Identifying hit compounds is an important step in drug development. Unfortunately, this process continues to be a challenging task. Several machine learning models have been generated to aid in simplifying and improving the prediction ...

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• A dataset containing more than 6,500,000 bioactive data was curated.
• More than ...

Accurate identification of gene modules based on biological networks is an effective approach to understanding gene patterns of cancer from a module-level perspective. However, most graph clustering algorithms just consider low-order ...

• The method focuses on the critical role of multi-order similarity for module identification and proposes an innovative graph convolution strategy to obtain ...

In this work, we present a deep reinforcement learning-based approach as a baseline system for autonomous propofol infusion control. Specifically, design an environment for simulating the possible conditions of a target patient based ...

Cardiovascular diseases (CVD), as the leading cause of death in the world, poses a serious threat to human health. The segmentation of carotid Lumen-intima interface (LII) and Media-adventitia interface (MAI) is a prerequisite for ...

• We Propose a novel nested DCNN model for accurate segmentation of LII and MAI.
• ...

The coronary arteries supply blood to the myocardium, which originate from the root of the aorta and mainly branch into the left and right. X-ray digital subtraction angiography (DSA) is a technique for evaluating coronary artery ...

• Semi-supervised learning (SSL) method using two different networks were adopted to segment coronary arteries.

Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease diagnosis with their outstanding image classification performance. In spite of the outstanding results, the widespread adoption of these ...

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• A survey of the Explainable Artificial Intelligence (XAI) techniques for biomedical imaging.