Practice Management

DCACNet: Dual context aggregation and attention-guided cross deconvolution network for medical image segmentation.

BACKGROUND AND OBJECTIVE: Segmentation is a key step in biomedical image analysis tasks. Recently, convolutional neural networks (CNNs) have been increasingly applied in the field of medical image processing; however, standard models still have some drawbacks. Due to the significant loss of spatial information at the coding stage, it is often difficult to restore the details of low-level visual fe...

Research on the Interaction of Genetic Algorithm in Assisted Composition.

Computer-aided composition is an attempt to use a formalized process to minimize human (or composer) involvement in the creation of music using a computer. Exploring the problem of computer-aided composition can enable us to understand and simulate the thinking mode of composers in the special process of music creation, which is an important application of artificial intelligence in the field of a...

Image Processing Technology in Remote Monitoring and Intelligent Medical System.

In order to study the application of image processing technology in remote monitoring and intelligent medical systems, the principle and implementatio...

Non-invasive diagnosis of Crohn's disease based on SERS combined with PCA-SVM.

Crohn's disease (CD) is an idiopathic chronic inflammatory bowel disease without a cure. Most of the CD patients are firstly diagnosed by invasive end...

Visual prototypes in the ventral stream are attuned to complexity and gaze behavior.

Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concen...

An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford.

Deep learning models can recognize the food item in an image and derive their nutrition information, including calories, macronutrients (carbohydrates...

Efficacy and Safety of Appropriate Shocks and Antitachycardia Pacing in Transvenous and Subcutaneous Implantable Defibrillators: Analysis of All Appropriate Therapy in the PRAETORIAN Trial.

BACKGROUND: The PRAETORIAN trial (A Prospective, Randomized Comparison of Subcutaneous and Transvenous Implantable Cardioverter Defibrillator Therapy)...

ICD-11: an international classification of diseases for the twenty-first century.

BACKGROUND: The International Classification of Diseases (ICD) has long been the main basis for comparability of statistics on causes of mortality and...

Artificial Intelligence of Things (AIoT) Enabled Floor Monitoring System for Smart Home Applications.

To enable smart homes and relative applications, the floor monitoring system with embedded triboelectric sensors has been proven as an effective parad...

Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy.

BACKGROUND: Patients with an implantable cardioverter-defibrillator (ICD) are at a high risk of malignant ventricular arrhythmias. The use of remote I...

Protein Abundance Prediction Through Machine Learning Methods.

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, abs...

An Intelligent Control Model of Credit Line Computing in Intelligence Health-Care Systems.

Technologies such as machine learning and artificial intelligence have brought about a tremendous change to biomedical computing and intelligence heal...

Dual coding of knowledge in the human brain.

How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human la...

Machine learning approach to measurement of criticism: The core dimension of expressed emotion.

Expressed emotion (EE), a measure of the family's emotional climate, is a fundamental measure in caregiving research. A core dimension of EE is the le...

Deep learning methods for screening patients' S-ICD implantation eligibility.

Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T ...

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestation...

Automated ICD coding for primary diagnosis via clinically interpretable machine learning.

BACKGROUND: Computer-assisted clinical coding (CAC) based on automated coding algorithms has been expected to improve the International Classification...

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The dis...

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning.

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abun...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete....