ICBBT

The corona virus responsible for COVID-19 has come into our lives with huge stampede. Every human activity has been seriously hurt and millions were confined to their homes. As of March, people in Europe wonder whether the confinement, closures and no-...

The discriminatory capability of multiple obesity indicators for cardiovascular disease (CVD) risk remains uncertain. The purpose of this study was to find the best indicator(s) of obesity among these anthropometric parameters for assessing ...

Finding a tool to diagnose the correlation of obesity with arteriosclerosis is very important. We analyzed the relationship between different anthropometric and body-composition parameters with arterial stiffness (AS) in middle-aged and elderly people. ...

About 80% of liver cancer cases were hepatocellular carcinoma. To explore the pathogenesis of hepatocellular carcinoma, a bioinformatics algorithm based on gene co-expression network analysis was used to study the gene expression data of hepatocellular ...

Stroke ranks second after heart disease as a cause of disability in high-income countries and as a cause of death worldwide. Identifying the biomarkers of ischemic stroke is possible to help diagnose stroke cases from non-stroke cases, as well as ...

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory system disease with high mortality rates. COPD has a tendency of family aggregation, and is often caused by the accumulation of multiple genes interaction and environmental factors. ...

This research paper proposes early detection of epileptic signal using wearable sensor and signal is transmitted to smartphone. In smartphone, by using machine learning algorithm which works on EEG signal and after processing, it with machine learning ...

Efficient control of bioprocess is becoming more and more relevant in today's biotechnology industry and environment of changing technologies. Many of important bioprocess variables are not measured on-line. Usually it took 15 min and some of them only ...

Protein-ligand docking is an important and effective structure-based drug design method widely used for large-scale screening of drug candidates. The core of a protein-ligand docking program consists of a sampling algorithm and a scoring function, which ...

The shortest path problem in graphs is a famous NP-complete problem, and the traditional use of computer algorithms to solve this problem has great limitations. Based on the nanopore detections of parallelism and programmable DNA assembly strategy, this ...

Peptide-binding proteins are excessive in living cells and proteinpeptide interactions mediate a wide range of cellular functions. Prediction of protein-peptide binding residues has been vital and popular in the past decades and machine learning methods ...

Volume rendering is a key visualization technology in the medical field. It is often used to observe medical volumes such as CTs and MRIs, but the rendering results may not present multiple regions of interest (ROIs) well. In order to solve this problem,...

Circulating tumor cell (CTC) detection is used to identify malignant tumor cells that are disseminated in the patient's circulating blood. It has been widely used in early tumor classification, prognosis judgment and efficacy evaluation. It also plays ...

The magnetoacoustic tomography with magnetic induction (MAT-MI) is a noninvasive imaging method which can reflect the conductivity distribution of the imaging target, and has broad application in early diseases diagnosis. Most previous studies of MAT-MI ...

The technology expansion in medical imaging has been become important part of clinical practice particularly in interdisciplinary research field. A computer aided diagnostic processing has crucially contribute to the development of algorithm and ...

Diabetic retinopathy is the most dangerous frequent fundus disease. Diabetic retinopathy can result in many serious diseases. For various reasons, patients lose a vision because of untimely or incorrect treatment of diabetic retinopathy. The modern ...

Currently, evaluation of abnormal lesions on lung Computed Tomography (CT) images is an important step, especially in patients who have tumor in the early stages, leading to increased survival rates. In early cases of tumor diagnosis on lung, Positron ...

Given the current relevance of deep learning approaches, their use in segmentation tasks and the fact that they can learn to segment from examples, it is important to assess the quality of the result. In this work we do an assessment of the quality of ...

In this paper, according to the treatment status of keratoconus and the principle of projection optical system, the corneal crosslinker optical system was designed to cover the single eye with uniform and variable shape. Firstly, this paper presents the ...

This paper proposes a method to differentiate accurately and rapidly Ipomoea spp, a weed, from sugar cane plantation. Weeds compete for water and nutrients with sugar cane thus Ipomoea spp causes losses to production. Ipomoea spp is dicotyledon and ...

To a certain extent, modern aesthetics force people to change the shape and color of eyebrows according to the current popular form, and achieve the aesthetic effect of the overall effect. How to match the appropriate eyebrows according to different ...

Monocytes/macrophages are critical inflammatory components predominantly recruited to tumor tissue to facilitate tumor metastasis. However, the underlying regulatory mechanisms remain largely unclear. In the study, we show that tumor-secreted soluble ...

Helicobacter pylori induce inflammation and gastric mucosal injury. Inflammation is characterized by increased activity of pro-inflammatory cytokines; those are controlled and stimulated by macrophage migration inhibitory factor (MIF). Gastric injury, ...

The main purpose of this simulation study was to estimate the effect of muscle fibres inclination on the degree of Gaussianity of the surface electromyographic (sEMG) signals generated in a cylindrical multilayer volume conductor constituted by bone, ...

Recent work suggests that machine and deep learning models are prone to EEG artifacts and have staggering performance drops when used to classify EEG signals rich of noise. This particularly affects real-time performance of EEG monitoring systems such ...

Surface electromyographic (sEMG) signals contain rich motion information, which could be used for motion recognition and activities of daily living detection. The study analyzed the possibility of classifying the various reaching patterns in a ...