Employing feature engineering strategies to improve the performance of machine learning algorithms on echocardiogram dataset.

Objectives: This study mainly uses machine learning (ML) to make predictions by inputting features during training and inference. The method of feature selection is an important factor affecting the accuracy of ML models, and the process includes data extraction, which is the collection of all data required for ML. It also needs to import the concept of feature engineering, namely, this study needs to label the raw data of the cardiac ultrasound dataset with one or more meaningful and informative labels so that the ML model can learn from it and predict more accurate target values.

Image segmentation using transfer learning and Fast R-CNN for diabetic foot wound treatments.

Diabetic foot ulcers (DFUs) are considered the most challenging forms of chronic ulcerations to handle their multifactorial nature. It is necessary to establish a comprehensive treatment plan, accurate, and systematic evaluation of a patient with a DFU. This paper proposed an image recognition of diabetic foot wounds to support the effective execution of the treatment plan.

Classification of Dementia Severity in Taiwan Based on History-Based Clinical Diagnosis System.

Background/aims: This study used HAICDDS screening questionnaire to classify the severity of dementia in Taiwan based on the clinical dementia rating scale.

Methods: LDA was applied to 6,328 Taiwanese clinical patients for classification purposes. Clustering method was used to identify the associated influential symptoms for each severity level.

CUX2, BRAP and ALDH2 are associated with metabolic traits in people with excessive alcohol consumption.

Molecular mechanisms that prompt or mitigate excessive alcohol consumption could be partly explained by metabolic shifts. This genome-wide association study aims to identify the susceptibility gene loci for excessive alcohol consumption by jointly measuring weekly alcohol consumption and γ-GT levels. We analysed the Taiwan Biobank data of 18,363 Taiwanese people, including 1945 with excessive alcohol use.

Correction: Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images.

[This corrects the article DOI: 10.1371/journal.pone.

ECG Sensor Card with Evolving RBP Algorithms for Human Verification.

It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy.

Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance.

Hiding patients confidential datainthe ECG signal viaa transform-domain quantization scheme.

Watermarking is the most widely used technology in the field of copyright and biological information protection. In this paper, we use quantization based digital watermark encryption technology on the Electrocardiogram (ECG) to protect patient rights and information. Three transform domains, DWT, DCT, and DFT are adopted to implement the quantization based watermarking technique.

Wavelet-based watermarking and compression for ECG signals with verification evaluation.

In the current open society and with the growth of human rights, people are more and more concerned about the privacy of their information and other important data. This study makes use of electrocardiography (ECG) data in order to protect individual information. An ECG signal can not only be used to analyze disease, but also to provide crucial biometric information for identification and authentication.

Computer-assisted system with multiple feature fused support vector machine for sperm morphology diagnosis.

Sperm morphology is an important technique in identifying the health of sperms. In this paper we present a new system and novel approaches to classify different kinds of sperm images in order to assess their health. Our approach mainly relies on a one-dimensional feature which is extracted from the sperm's contour with gray level information.

A new noninvasive approach to detect the artery's pulsating properties via tissue control method.

This paper presents a new approach, named as Tissue Control Method, to obtain the pulsating properties for artery. These properties are the variations of blood vessel diameter, instantaneous intra-arterial blood pressure, and the dynamic impedances of blood vessel. By maintaining the stiffness of tissue and tracking the variations of blood pressure at a critical location, it decouples the effect of the arterial pulsation from the tissue and measures the variations of the blood vessel diameter.

On measuring the instantaneous blood pressure in an artery via the tissue control method.

This paper presents a non-invasive approach to measuring the instantaneous arterial blood pressure based upon the tissue control method. According to animal experiments, there exists a pressed location where the mean blood pressure in the artery is equivalent to the mean pressure measured on the skin. At this location, the stiffness measured on the skin is equivalent to the stiffness of the tissue only.

Conceptual design of a multi-functional sphygmus detection system.

From the energy point of view, obtaining simultaneous blood pressure and flow rate of the radial artery at the wrist is very important for sphygmic diagnosis in medicine. This work depicts the conceptual design for a noninvasive multi-functional sphygmus detection system. According to Y.