Revolutionizing healthcare: the role of artificial intelligence in clinical practice

BMC Medical Education, Journal Year: 2023, Volume and Issue: 23(1)

Published: Sept. 22, 2023

Abstract Introduction Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI’s role in practice is crucial successful implementation equipping providers essential knowledge tools. Research Significance This review article provides a comprehensive up-to-date overview current state practice, its applications disease diagnosis, treatment recommendations, engagement. It also discusses associated challenges, covering ethical legal considerations need human expertise. By doing so, enhances understanding significance supports organizations effectively adopting technologies. Materials Methods The investigation analyzed use system relevant indexed literature, such as PubMed/Medline, Scopus, EMBASE, no time constraints limited articles published English. focused question explores impact applying settings outcomes this application. Results Integrating holds excellent improving selection, laboratory testing. tools leverage large datasets identify patterns surpass performance several aspects. offers increased accuracy, reduced costs, savings while minimizing errors. personalized medicine, optimize medication dosages, enhance population health management, establish guidelines, provide virtual assistants, support mental care, education, influence patient-physician trust. Conclusion be used diagnose diseases, develop plans, assist clinicians decision-making. Rather than simply automating tasks, about developing technologies that across settings. However, challenges related data privacy, bias, expertise must addressed responsible effective healthcare.

Language: Английский

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Tribulations and future opportunities for artificial intelligence in precision medicine

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: April 30, 2024

Abstract Upon a diagnosis, the clinical team faces two main questions: what treatment, and at dose? Clinical trials' results provide basis for guidance support official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate reported response from relevant trials. The decision complexity increases with combination treatments where drugs administered together can interact each other, which is often case. Additionally, individual's treatment varies changes in condition. In practice, drug dose selection depend significantly on medical protocol team's experience. As such, are inherently varied suboptimal. Big data Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit application. AI rapidly evolving dynamic field potential revolutionize various aspects of human life. has become increasingly crucial discovery development. enhances across different disciplines, such medicinal chemistry, molecular cell biology, pharmacology, pathology, practice. addition these, contributes patient population stratification. need healthcare evident it aids enhancing accuracy ensuring quality care necessary effective treatment. pivotal improving success rates increasing significance discovery, development, trials underscored by many scientific publications. Despite numerous advantages AI, advancing Precision Medicine (PM) remote monitoring, unlocking its full requires addressing fundamental concerns. These concerns include quality, lack well-annotated large datasets, privacy safety issues, biases algorithms, legal ethical challenges, obstacles related cost implementation. Nevertheless, integrating medicine will improve diagnostic outcomes, contribute more efficient delivery, reduce costs, facilitate better experiences, making sustainable. This article reviews applications development sustainable, highlights limitations applying AI.

Language: Английский

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Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Feb. 5, 2024

Abstract Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical from diagnostic domains such as clinical imaging, pathology, next-generation sequencing (NGS), which help characterize individual differences patients. However, this information needs to be available suitable promote support scientific research technological development, supporting the effective adoption precision medicine approach practice. Digital biobanks can catalyze process, facilitating sharing curated standardized imaging data, clinical, pathological molecular crucial enable development comprehensive personalized data-driven disease management fostering predictive models. This work aims frame perspective, first by evaluating state standardization then identifying challenges proposing possible solution towards an integrative that guarantee suitability shared through digital biobank. Our analysis art shows presence use reference standards and, generally, repositories for each specific domain. Despite this, integration reproducibility numerical descriptors generated domain, e.g. radiomic, pathomic -omic features, is still open challenge. Based on cases scenarios, model, based JSON format, proposed address problem. Ultimately, how, with promotion efforts, biobank model become enabling technology study diseases technologies at service medicine.

Language: Английский

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Role of Fluid Dynamics in Infectious Disease Transmission: Insights from COVID-19 and Other Pathogens

Trends in Sciences, Journal Year: 2024, Volume and Issue: 21(8), P. 8287 - 8287

Published: June 1, 2024

The spread of infectious diseases such as COVID-19 depends on complex fluid dynamics interactions between pathogens and phases, including individual droplets multiphase clouds. Understanding these is crucial for predicting controlling disease spread. This applies to human animal exhalations, coughs sneezes, well bursting bubbles that create micron-sized in various indoor outdoor environments. By exploring case studies this regard, study examines the emerging field transmission, focusing flows, interfacial turbulence, pathogens, traffic, aerosol ventilation, breathing microenvironments. These results indicate increased ventilation rates local methods can effectively reduce concentration SARS-CoV-2-laden aerosols immediate spaces individuals. In a displacement-ventilated room, both neutral unstable conditions were more effective removing breathed from air, regardless presence test subjects. However, stable may increase risk infection individuals living confined spaces. Thus, findings are useful providing practical guidance managing airborne infections. HIGHLIGHTS Fluid affect transmission explored flow, dispersion, respiratory zones Increased SARS-CoV-2 Displacement eliminates under Cramped damp environments GRAPHICAL ABSTRACT

Language: Английский

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Network-based drug repurposing identifies small molecule drugs as immune checkpoint inhibitors for endometrial cancer

Molecular Diversity, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 16, 2024

Language: Английский

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A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Journal of Biomedical Informatics, Journal Year: 2023, Volume and Issue: 142, P. 104373 - 104373

Published: April 27, 2023

Cancer is the second leading cause of death globally, trailing only heart disease. In United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, success rate drug development remains less than 10%, making disease particularly challenging. This low largely attributed to complex poorly understood nature etiology. Therefore, it critical find alternative approaches understanding biology developing effective treatments. One such approach repurposing, which offers a shorter timeline lower costs while increasing likelihood success. this review, we provide comprehensive analysis computational biology, including systems multi-omics, pathway analysis. Additionally, examine use these methods repurposing in cancer, databases tools that are used research. Finally, present case studies discussing their limitations offering recommendations future research area.

Language: Английский

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Revolutionizing drug development: harnessing the potential of organ-on-chip technology for disease modeling and drug discovery

Frontiers in Pharmacology, Journal Year: 2023, Volume and Issue: 14

Published: April 25, 2023

The inefficiency of existing animal models to precisely predict human pharmacological effects is the root reason for drug development failure. Microphysiological system/organ-on-a-chip technology (organ-on-a-chip platform) a microfluidic device cultured with living cells under specific organ shear stress which can faithfully replicate organ-body level pathophysiology. This emerging organ-on-chip platform be remarkable alternative broad range purposes in testing and precision medicine. Here, we review parameters employed using on chip as plot mimic diseases, genetic disorders, toxicity different organs, biomarker identification, discoveries. Additionally, address current challenges that should overcome accepted by regulatory agencies pharmaceutical industries. Moreover, highlight future direction enhancing accelerating discoveries personalized

Language: Английский

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CT-based delta-radiomics nomogram to predict pathological complete response after neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma patients

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: June 18, 2024

Abstract Background This study developed a nomogram model using CT-based delta-radiomics features and clinical factors to predict pathological complete response (pCR) in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiotherapy (nCRT). Methods The retrospectively analyzed 232 ESCC who underwent pretreatment post-treatment CT scans. Patients were divided into training (n = 186) validation 46) sets through fivefold cross-validation. 837 radiomics extracted from regions of interest (ROIs) delineations on images before after nCRT calculate delta values. LASSO algorithm selected (DRF) based classification performance. Logistic regression constructed incorporating DRFs factors. Receiver operating characteristic (ROC) area under the curve (AUC) analyses evaluated performance for predicting pCR. Results No significant differences existed between datasets. 4-feature signature (DRS) demonstrated good predictive accuracy pCR, with α-binormal-based empirical AUCs 0.871 0.869. T-stage ( p 0.001) differentiation degree 0.018) independent predictors combined DRS improved dataset (AUC αbin 0.933 AUC emp 0.941). set showed similar 0.958 0.962. Conclusions provided high pCR nCRT.

Language: Английский

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Data Management in Biobanking: Strategies, Challenges, and Future Directions

BioTech, Journal Year: 2024, Volume and Issue: 13(3), P. 34 - 34

Published: Sept. 2, 2024

Biobanking plays a pivotal role in biomedical research by providing standardized processing, precise storing, and management of biological sample collections along with the associated data. Effective data is prerequisite to ensure integrity, quality, accessibility these resources. This review provides current landscape biobanking, discussing key challenges, existing strategies, potential future directions. We explore multiple aspects management, including collection, storage, curation, sharing, ethical considerations. By examining evolving technologies methodologies we aim provide insights into addressing complexities maximizing utility biobank for clinical applications.

Language: Английский

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Single-cell atlas reveals multi-faced responses of losartan on tubular mitochondria in diabetic kidney disease

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: Jan. 21, 2025

Mitochondria are crucial to the function of renal tubular cells, and their dynamic perturbation in many aspects is an important mechanism diabetic kidney disease (DKD). Single-nucleus RNA sequencing (snRNA-seq) technology a high-throughput analysis technique for at level single cell nucleus. Here, our DKD mouse single-cell conveys more comprehensive mitochondrial profile, which helps us further understand therapeutic response this unique organelle family drugs. After high fat diet (HFD), mice were intraperitoneally injected with streptozotocin (STZ) induce DKD, then divided into three subsets: CON (healthy) subset, (vehicle) LST (losartan; 25 mg/kg/day) subset. Divide HK-2 LG (low glucose; 5 mM) HG (high 30 + 1 µ M) subsets. snRNA-seq was performed on tissues subset mice. To reveal effects losartan gene pathway changes mitochondria, Gene Ontology (GO) enrichment GSEA/GSVA scoring analyze specific proximal (PT) mitochondria treatment, including key events homeostasis such as morphology, dynamics, mitophagy, autophagic flux, respiratory chain, apoptosis, ROS generation. Preliminary validation through vitro vivo experiments, observation morphology dynamics using probes Mitotracker Red, evaluation effect electron microscopy, laser confocal immunofluorescence, Western blotting. Detection flux cells by transfecting Ad-mCherry-GFP-LC3B dual fluorescence labeled adenovirus. Various fluorescent energy detector used detect ROS, respiration mitochondrion. Through atlas kidneys, it found that treatment significantly increased percentage PT cells. differentially expressed genes showed autophagy mitochondrion pathway. Further GSEA GSVA revealed mitophagy other events, production, membrane potential, adenosine triphosphate (ATP) synthesis, involved protective thereby improving homeostasis. Consistent results also obtained cellular experiments. In addition, we highlighted subpopulation phenotype data, preliminarily validated co-localization expression Pink1 Gclc specimens patients treated losartan. Our research suggests scRNA-seq can reflect multifaceted landscape after drug these findings may provide new targets therapy level.

Language: Английский

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