Medical and Biological Engineering and Computing Medical and Biological Engineering and Computing RSS feedThis is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Study on mechanical properties of dual-channel cryogenic 3D printing scaffold for mandibular defect repair
AbstractMandibular defect repair has always been a clinical challenge, facing technical bottleneck. The new materials directly affect technological breakthroughs in mandibular defect repair field. Our aim is to fabricate a scaffold of advanced biomaterials for repairing of small mandibular defect. Therefore, a novel dual-channel scaffold consisting of silk fibroin/collagen type-I/hydroxyapatite (SCH) and polycaprolactone/hydroxyapatite (PCL/HA) was fabricated by cryogenic 3D printing technology with double nozzles. The mechanical properties and behaviors of the dual-channel scaffold were investigated by performing uniaxial...
Source: Medical and Biological Engineering and Computing - April 16, 2024 Category: Biomedical Engineering Source Type: research

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets
AbstractUnderstanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-base...
Source: Medical and Biological Engineering and Computing - April 16, 2024 Category: Biomedical Engineering Source Type: research

Intelligent salivary biosensors for periodontitis: in vitro simulation of oral oxidative stress conditions
This study focused on hydrogen peroxide, lipopolysaccharide (LPS), and lactic acid as salivary non-protein biomarkers for oxidative stress conditions of periodontitis. Electrochemical analysis of artificial saliva was done using Gamry with increasing hydrogen peroxide, bLPS, and lactic acid concentrations. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were conducted. From EIS data, change in capacitance and CV plot area were calculated for each test condition. Hydrogen peroxide groups had a decrease in CV area and an increase in percentage change in capacitance, lipopolysaccharide groups had a de...
Source: Medical and Biological Engineering and Computing - April 13, 2024 Category: Biomedical Engineering Source Type: research

Lung pneumonia severity scoring in chest X-ray images using transformers
AbstractTo create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource-intensive training for optimal results. Healthcare practitioners require efficient computational tools to swiftly identify COVID-19 cases and predict the severity of the condition. In this research, we introduce a novel image augmentation scheme as well as a neural network model founded on Vision Transformers (ViT) with a small number of trainable parameters for quantify...
Source: Medical and Biological Engineering and Computing - April 9, 2024 Category: Biomedical Engineering Source Type: research

Analysis of reading-task-based brain connectivity in dyslexic children using EEG signals
In conclusion, the present study identified distinct graph measures between groups when performing a reading task and showed possible evidence for compromised brain networks in dyslexic group.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - April 8, 2024 Category: Biomedical Engineering Source Type: research

Nucleus segmentation of white blood cells in blood smear images by modeling the pixels ’ intensities as a set of three Gaussian distributions
AbstractThe precise segmentation of white blood cells (WBCs) within blood smear images is a significant challenge with implications for both medical research and image processing. Of particular importance is the often neglected task of accurately segmenting WBC nuclei, an aspect that currently lacks dedicated methodologies. This paper introduces a straightforward and efficient method designed to fill this critical gap, providing an effective solution for the efficient segmentation of WBC nuclei. In blood smear imagery, the distinctive coloration of WBCs contrasts with the hues of other blood components. The inherent obscur...
Source: Medical and Biological Engineering and Computing - April 8, 2024 Category: Biomedical Engineering Source Type: research

Predicting ischemic stroke patients ’ prognosis changes using machine learning in a nationwide stroke registry
This study aimed to overcome these gaps by utilizing a large national stroke registry database to assess various prediction models that estimate how patients ’ prognosis changes over time with associated clinical factors. To properly evaluate the best predictive approaches currently available and avoid prejudice, this study employed three different prognosis prediction models including a statistical logistic regression model, commonly used clinical-bas ed scores, and a latest high-performance ML-based XGBoost model. The study revealed that the XGBoost model outperformed other two traditional models, achieving an AUROC of...
Source: Medical and Biological Engineering and Computing - April 5, 2024 Category: Biomedical Engineering Source Type: research

A novel machine learning model for breast cancer detection using mammogram images
AbstractThe most fatal disease affecting women worldwide now is breast cancer. Early detection of breast cancer enhances the likelihood of a full recovery and lowers mortality. Based on medical imaging, researchers from all around the world are developing breast cancer screening technologies. Due to their rapid progress, deep learning algorithms have caught the interest of many in the field of medical imaging. This research proposes a novel method in mammogram image feature extraction with classification and optimization using machine learning in breast cancer detection. The input image has been processed for noise removal...
Source: Medical and Biological Engineering and Computing - April 5, 2024 Category: Biomedical Engineering Source Type: research

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database
This study aimed to establish the generalizability of previous institutionally developed ML models to predict 30-day readmission following primary TKA using a national database. Data from 424,354 patients from the ACS-NSQIP database was used to develop and validate four ML models to predict 30-day readmission risk after primary TKA. Individual model performance was assessed and compared based on discrimination, accuracy, calibration, and clinical utility. Length of stay (>  2.5 days), body mass index (BMI) (>  33.21 kg/m2), and operation time (>  93 min) were important determinants of 30-day readmission. ...
Source: Medical and Biological Engineering and Computing - April 1, 2024 Category: Biomedical Engineering Source Type: research

When deep learning is not enough: artificial life as a supplementary tool for segmentation of ultrasound images of breast cancer
AbstractSegmentation of tumors in ultrasound (US) images of the breast is a critical issue in medical imaging. Due to the poor quality of US images and the varying specifications of US machines, segmentation and classification of abnormalities present difficulties even for trained radiologists. The paper aims to introduce a novel AI-based hybrid model for US segmentation that offers high accuracy, requires relatively smaller datasets, and is capable of handling previously unseen data. The software can be used for diagnostics and the US-guided biopsies. A unique and robust hybrid approach that combines deep learning (DL) an...
Source: Medical and Biological Engineering and Computing - March 18, 2024 Category: Biomedical Engineering Source Type: research

Numerical study of the induction of intratumoral apoptosis under microwave ablation by changing slot length of microwave coaxial antenna
This study confirmed optimal therapeutic conditions for MWA. Three apoptotic variables were used to quantitatively identify apoptotic temperature maintenance inside tumor tissue and thermal damage to surrounding normal tissue. The findings of this study are expected to serve as a standard for treatment based on actual MWA treatment.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - March 15, 2024 Category: Biomedical Engineering Source Type: research

Advancing brain tumor classification through MTAP model: an innovative approach in medical diagnostics
AbstractThe early diagnosis of brain tumors is critical in the area of healthcare, owing to the potentially life-threatening repercussions unstable growths within the brain can pose to individuals. The accurate and early diagnosis of brain tumors enables prompt medical intervention. In this context, we have established a new model called MTAP to enable a highly accurate diagnosis of brain tumors. The MTAP model addresses dataset class imbalance by utilizing the ADASYN method, employs a network pruning technique to reduce unnecessary weights and nodes in the neural network, and incorporates Avg-TopK pooling method for enhan...
Source: Medical and Biological Engineering and Computing - March 14, 2024 Category: Biomedical Engineering Source Type: research

On the uncertainty quantification of the active uterine contraction during the second stage of labor simulation
AbstractUterine contractions in the myometrium occur at multiple scales, spanning both organ and cellular levels. This complex biological process plays an essential role in the fetus delivery during the second stage of labor. Several finite element models of active uterine contractions have already been developed to simulate the descent of the fetus through the birth canal. However, the developed models suffer severe reliability issues due to the uncertain parameters. In this context, the present study aimed to perform the uncertainty quantification (UQ) of the active uterine contraction simulation to advance our understan...
Source: Medical and Biological Engineering and Computing - March 13, 2024 Category: Biomedical Engineering Source Type: research

An AI healthcare ecosystem framework for Covid-19 detection and forecasting using CronaSona
AbstractThe primary purpose of this paper is to establish a healthcare ecosystem framework for COVID-19, CronaSona. Unlike some studies that focus solely on detection or forecasting, CronaSona aims to provide a holistic solution, for managing data and/or knowledge, incorporating detection, forecasting, expert advice, treatment recommendations, real-time tracking, and finally visualizing results. The innovation lies in creating a comprehensive healthcare ecosystem framework and an application that not only aids in COVID-19 diagnosis but also addresses broader health challenges. The main objective is to introduce a novel fra...
Source: Medical and Biological Engineering and Computing - March 13, 2024 Category: Biomedical Engineering Source Type: research

Image reconstruction method for incomplete CT projection based on self-guided image filtering
AbstractIn some fields of medical diagnosis or industrial nondestructive testing, it is difficult to obtain complete computed tomography (CT) data due to the limitation of radiation dose or other factors. Therefore, image reconstruction of incomplete projection data is the focus of this paper. In this paper, a new image reconstruction model based on self-guided image filtering (SGIF) term is proposed for few-view and segmental limited-angle (SLA) CT reconstruction. Then the alternating direction method (ADM) is used to solve this model. For simplicity, we call it ADM-SGIF method. The key idea of ADM-SGIF method is to use t...
Source: Medical and Biological Engineering and Computing - March 8, 2024 Category: Biomedical Engineering Source Type: research