Machine learning-based heart disease diagnosis: A systematic literature review
Heart disease is one of the significant challenges in today's world and one of the leading
causes of many deaths worldwide. Recent advancement of machine learning (ML) …
causes of many deaths worldwide. Recent advancement of machine learning (ML) …
Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review
Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
The significance of machine learning in clinical disease diagnosis: A review
The global need for effective disease diagnosis remains substantial, given the complexities
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
Deep learning in multi-class lung diseases' classification on chest X-ray images
Chest X-ray radiographic (CXR) imagery enables earlier and easier lung disease diagnosis.
Therefore, in this paper, we propose a deep learning method using a transfer learning …
Therefore, in this paper, we propose a deep learning method using a transfer learning …
Deep Learning-Based Sensor Array: 3D Fluorescence Spectra of Gold Nanoclusters for Qualitative and Quantitative Analysis of Vitamin B6 Derivatives
HAA Noreldeen, KY Huang, GW Wu, HP Peng… - Analytical …, 2022 - ACS Publications
Vitamin B6 derivatives (VB6Ds) are of great importance for all living organisms to complete
their physiological processes. However, their excess in the body can cause serious …
their physiological processes. However, their excess in the body can cause serious …
Medical long-tailed learning for imbalanced data: bibliometric analysis
Background In the last decade, long-tail learning has become a popular research focus in
deep learning applications in medicine. However, no scientometric reports have provided a …
deep learning applications in medicine. However, no scientometric reports have provided a …
A personalized zero-shot ecg arrhythmia monitoring system: From sparse representation based domain adaption to energy efficient abnormal beat detection for …
This paper proposes a low-cost and highly accurate ECG-monitoring system intended for
personalized early arrhythmia detection for wearable mobile sensors. Earlier supervised …
personalized early arrhythmia detection for wearable mobile sensors. Earlier supervised …
Deep learning-based text emotion analysis for legal anomie
B She - Frontiers in Psychology, 2022 - frontiersin.org
Text emotion analysis is an effective way for analyzing the emotion of the subjects' anomie
behaviors. This paper proposes a text emotion analysis framework (called BCDF) based on …
behaviors. This paper proposes a text emotion analysis framework (called BCDF) based on …
A micro neural network for healthcare sensor data stream classification in sustainable and smart cities
A smart city is an intelligent space, in which large amounts of data are collected and
analyzed using low‐cost sensors and automatic algorithms. The application of artificial …
analyzed using low‐cost sensors and automatic algorithms. The application of artificial …
Digital filtering techniques using fuzzy-rules based logic control
This paper discusses current formulations based on fuzzy-logic control concepts as applied
to the removal of impulsive noise from digital images. We also discuss the various principles …
to the removal of impulsive noise from digital images. We also discuss the various principles …