Parrot optimizer: Algorithm and applications to medical problems

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 172, P. 108064 - 108064

Published: Feb. 24, 2024

Language: Английский

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AI-enabled organoids: Construction, analysis, and application

Bioactive Materials, Journal Year: 2023, Volume and Issue: 31, P. 525 - 548

Published: Sept. 16, 2023

Organoids, miniature and simplified

Language: Английский

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The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(11), P. 5757 - 5797

Published: Jan. 13, 2024

Abstract Nowadays, machine learning (ML) has attained a high level of achievement in many contexts. Considering the significance ML medical and bioinformatics owing to its accuracy, investigators discussed multiple solutions for developing function challenges using deep (DL) techniques. The importance DL Internet Things (IoT)-based bio- informatics lies ability analyze interpret large amounts complex diverse data real time, providing insights that can improve healthcare outcomes increase efficiency industry. Several applications IoT-based include diagnosis, treatment recommendation, clinical decision support, image analysis, wearable monitoring, drug discovery. review aims comprehensively evaluate synthesize existing body literature on applying intersection IoT with informatics. In this paper, we categorized most cutting-edge issues into five categories based technique utilized: convolutional neural network , recurrent generative adversarial multilayer perception hybrid methods. A systematic was applied study each one terms effective properties, like main idea, benefits, drawbacks, methods, simulation environment, datasets. After that, research approaches concerns emphasized. addition, several contributed implementation have been addressed, which are predicted motivate more studies develop progressively. According findings, articles evaluated features sensitivity, specificity, F -score, latency, adaptability, scalability.

Language: Английский

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Synthesis, molecular docking and DFT analysis of novel bis-Schiff base derivatives with thiobarbituric acid for α-glucosidase inhibition assessment

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 10, 2024

Abstract A library of novel bis -Schiff base derivatives based on thiobarbituric acid has been effectively synthesized by multi-step reactions as part our ongoing pursuit anti-diabetic agents. All these were subjected to in vitro α-glucosidase inhibitory potential testing after structural confirmation modern spectroscopic techniques. Among them, compound 8 (IC 50 = 0.10 ± 0.05 µM), and 9 0.13 0.03 µM) exhibited promising activity better than the standard drug acarbose 0.27 0.04 µM). Similarly, ( 5 , 6 7 10 4 ) showed significant good range IC values from 0.32 0.52 0.02 µM. These docked with target protein elucidate their binding affinities key interactions, providing additional insights into mechanisms. The chemical nature compounds reveal performing density functional theory (DFT) calculation using hybrid B3LYP 6-311++G(d,p) basis set. presence intramolecular H-bonding was explored DFT-d3 reduced gradient (RGD) analysis. Furthermore, various reactivity parameters TD-DFT at CAM-B3LYP/6-311++G(d,p) method.

Language: Английский

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Robust and Multifunctional Nanoparticles Assembled from Natural Polyphenols and Metformin for Efficient Spinal Cord Regeneration

ACS Nano, Journal Year: 2023, Volume and Issue: 17(18), P. 18562 - 18575

Published: Sept. 14, 2023

The treatment of spinal cord injury (SCI) remains unsatisfactory owing to the complex pathophysiological microenvironments at site and limited regenerative potential central nervous system. Metformin has been proven in clinical animal experiments repair damaged structures functions by promoting endogenous neurogenesis. However, early stage acute SCI, adverse microenvironment sites, such as reactive oxygen species inflammatory factor storm, can prevent activation neural stem cells (NSCs) differentiation NSCs into neurons, decreasing whole effect. To address those issues, a series robust multifunctional natural polyphenol-metformin nanoparticles (polyphenol-Met NPs) were fabricated with pH-responsiveness excellent antioxidative capacities. resulting NPs possessed several favorable advantages: First, composed active ingredients different biological properties, without need for carriers; second, feature could allow targeted drug delivery injured site; more importantly, enabled drugs performances exhibit strong synergistic effects. results demonstrated that improved polyphenols boosted activated neurons oligodendrocytes, which efficiently nerve enhance functional recovery SCI rats. This work highlighted design fabrication via efficient microenvironmental regulation activation.

Language: Английский

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Digital technologies in sports: Opportunities, challenges, and strategies for safeguarding athlete wellbeing and competitive integrity in the digital era

Technology in Society, Journal Year: 2024, Volume and Issue: 77, P. 102496 - 102496

Published: March 6, 2024

Language: Английский

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The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Transactions on Emerging Telecommunications Technologies, Journal Year: 2024, Volume and Issue: 35(6)

Published: May 21, 2024

Abstract Nature‐inspired algorithms revolve around the intersection of nature‐inspired and IoT within healthcare domain. This domain addresses emerging trends potential synergies between computational approaches technologies for advancing services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, efficacy IoT‐based healthcare. We provide insights into practical aspects limitations such applications through a systematic literature review. Specifically, we address need comprehensive understanding healthcare, identifying as lack standardized evaluation metrics studies on challenges security considerations. By bridging these gaps, our paper offers directions future this domain, exploring diverse landscape chosen methodology is Systematic Literature Review (SLR) investigate related papers rigorously. Categorizing groups genetic algorithms, particle swarm optimization, cuckoo ant colony other approaches, hybrid methods, employ meticulous classification based critical criteria. MATLAB emerges predominant programming language, constituting 37.9% cases, showcasing prevalent choice among researchers. emphasizes adaptability paramount parameter, accounting 18.4% shedding light attributes, limitations, development, review contribute dynamic

Language: Английский

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Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 20, 2024

Language: Английский

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Bioinformatics in bioscience and bioengineering: Recent advances, applications, and perspectives

Journal of Bioscience and Bioengineering, Journal Year: 2022, Volume and Issue: 134(5), P. 363 - 373

Published: Sept. 17, 2022

Language: Английский

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Improving Prediction of Cervical Cancer Using KNN Imputed SMOTE Features and Multi-Model Ensemble Learning Approach

Cancers, Journal Year: 2023, Volume and Issue: 15(17), P. 4412 - 4412

Published: Sept. 4, 2023

Objective: Cervical cancer ranks among the top causes of death females in developing countries. The most important procedures that should be followed to guarantee minimizing cervical cancer’s aftereffects are early identification and treatment under finest medical guidance. One best methods find this sort malignancy is by looking at a Pap smear image. For automated detection cancer, available datasets often have missing values, which can significantly affect performance machine learning models. Methods: To address these challenges, study proposes an system for predicting efficiently handles values with SMOTE features achieve high accuracy. proposed employs stacked ensemble voting classifier model combines three models, along KNN Imputer up-sampled handling values. Results: achieves 99.99% accuracy, precision, recall, F1 score when using imputed features. compares multiple other algorithms four scenarios: removed, imputation, features, validates efficacy against existing state-of-the-art approaches. Conclusions: This investigates issue class imbalance data collected might aid practitioners timely providing patients better care.

Language: Английский

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