AIMC Topic: Databases, Factual

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Augmenting biomedical named entity recognition with general-domain resources.

Journal of biomedical informatics
OBJECTIVE: Training a neural network-based biomedical named entity recognition (BioNER) model usually requires extensive and costly human annotations. While several studies have employed multi-task learning with multiple BioNER datasets to reduce hum...

De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.

Clinical orthopaedics and related research
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...

MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features.

Journal of imaging informatics in medicine
The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. This research introduces a novel skin disease classification model leveraging advanced deep learning techniques. The proposed architecture combines the M...

Visual interpretation of deep learning model in ECG classification: A comprehensive evaluation of feature attribution methods.

Computers in biology and medicine
Feature attribution methods can visually highlight specific input regions containing influential aspects affecting a deep learning model's prediction. Recently, the use of feature attribution methods in electrocardiogram (ECG) classification has been...

An Arrhythmia Classification Model Based on a CNN-LSTM-SE Algorithm.

Sensors (Basel, Switzerland)
Arrhythmia is the main cause of sudden cardiac death, and ECG signal analysis is a common method for the noninvasive diagnosis of arrhythmia. In this paper, we propose an arrhythmia classification model based on the combination of a channel attention...

Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

Computers in biology and medicine
OBJECTIVE: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

High-resolution AI image dataset for diagnosing oral submucous fibrosis and squamous cell carcinoma.

Scientific data
Oral cancer is a global health challenge with a difficult histopathological diagnosis. The accurate histopathological interpretation of oral cancer tissue samples remains difficult. However, early diagnosis is very challenging due to a lack of experi...

Applying machine learning approaches for predicting obesity risk using US health administrative claims database.

BMJ open diabetes research & care
INTRODUCTION: Body mass index (BMI) is inadequately recorded in US administrative claims databases. We aimed to validate the sensitivity and positive predictive value (PPV) of BMI-related diagnosis codes using an electronic medical records (EMR) clai...

No-reference stereoscopic image quality assessment based on binocular collaboration.

Neural networks : the official journal of the International Neural Network Society
Stereoscopic images typically consist of left and right views along with depth information. Assessing the quality of stereoscopic/3D images (SIQA) is often more complex than that of 2D images due to scene disparities between the left and right views ...