The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of Deep Bayesian Neural Network (DBNN) for the personalized treatment of leukemia cancer has shown a significant tested accuracy for the model. DBNNs used in this study was able to classify images with accuracy exceeding 98.73%. This study depicts that the DBNN can classify cell cultures only based on unstained light microscope images which allow their further use. Therefore, building a bayesian‐based model to great help during commercial cell culturing, and possibly a first step in the process of creating an automated/semiautomated neural network‐based model for classification of good and bad quality cultures when images of such will be available.
Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreThe rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
... Show MoreThis paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere
... Show MoreObjective: study aims to identify the diabetes type2 clients self management skills toward dietary pattern
, and find out the relationship between variables which are (Age, gender, educational level, duration of DM
diagnosis, and monthly income) with diabetes type 2 clients self management skills toward dietary pattern
Methodology: descriptive study was carried out through the present investigation from January 2nd
2011to September 2nd 2011 in order to achieve the objectives of the present study. A non probability
(purposive) sample, (200) cases which consists of clients who were attending Al-Nasiriyha diabetic center.
Including (118) males and (82) females. The data were collected by utilization of the study instrument
To assess the total hip replacement patients’ knowledge of home – care regarding pain management, medication therapy, wound care, mobility limitation and complications may occur in the post hip replacement surgery, and to assess relationship between some variables such as, age level of education, sex & marital status with home- care knowledge. A descriptive study was used to assess the hip-replacement patient home-knowledge, a purposive sampling of (60) hip-replaced –patients were selected from Gazy Alhariri Hospital (central of surgical profession ) and Alwasity Hospital ( plastic surgery) , the questionnaire obtains two parts , part one, which included socio-demographical characteristics of the samp
... Show MoreOver the past few decades, the global usage and applications of different kinds of complementary and alternative medicine are greatly exaggerated among the general population, this requires improving the knowledge of all health care provider including pharmacists toward proper and safe use of different complementary and alternative medicine modalities. The current study aims to assess the Iraqi pharmacists' knowledge, use, and recommendation toward complementary and alternative medicine A cross-sectional pilot survey was done on a convenient sample of Iraqi pharmacists. Data were collected using a pretested
The study aimed to compare the expression of miR-126-3p and miR-423-5p in patients and normal subjects, and correlate their expression with response to induction therapy. Circulating miR-126-3p and miR-423-5p were measured in the plasma of 43 adult AML patients and 35 age- and sex-matched controls by real time PCR. The foldchange in differential expression for each gene was calculated using the comparative cycle threshold (CT) method (also known as the 2−CT method). For statistical purposes, the fold change was calculated using DDCT (or 2–∆∆Ct) method to find the relative expression of miRNAs. The expression fold change of miR-126-3p was 1.73-fold increase in patients than controls (p= 0.010). The expression fold change of miR-423-5
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