Unveiling the Secrets of Acinetobacter baumannii: Resistance, Current Treatments, and Future Innovations

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(13), P. 6814 - 6814

Published: June 21, 2024

represents a significant concern in nosocomial settings, particularly critically ill patients who are forced to remain hospital for extended periods. The challenge of managing and preventing this organism is further compounded by its increasing ability develop resistance due extraordinary genomic plasticity, response adverse environmental conditions. Its recognition as public health risk has provided impetus the identification new therapeutic approaches infection control strategies. Indeed, currently used antimicrobial agents gradually losing their efficacy, neutralized newer mechanisms bacterial resistance, especially carbapenem antibiotics. A deep understanding underlying molecular urgently needed shed light on properties that allow

Language: Английский

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The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(2), P. 695 - 695

Published: Jan. 5, 2024

Even if malaria is rare in Europe, it a medical emergency and programs for its control should ensure both an early diagnosis prompt treatment within 24–48 h from the onset of symptoms. The increasing number imported cases as well risk reintroduction autochthonous encouraged laboratories non-endemic countries to adopt diagnostic methods/algorithms. Microscopy remains gold standard, but with limitations. Rapid tests have greatly expanded ability diagnose rapid results due simplicity low cost, they lack sensitivity specificity. PCR-based assays provide more relevant information need well-trained technicians. As reported World Health Organization Global Technical Strategy Malaria 2016–2030, development point-of-care testing important improvement beneficial consequences prompt/accurate preventing spread disease. Despite their limitations, methods contribute decline mortality. Recently, evidence suggested that artificial intelligence could be utilized assisting pathologists diagnosis.

Language: Английский

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Exploring the synergy of artificial intelligence in microbiology: Advancements, challenges, and future prospects

Deleted Journal, Journal Year: 2024, Volume and Issue: 1, P. 100005 - 100005

Published: June 1, 2024

The integration of artificial intelligence (AI) into microbiology has the transformative potential to advance our understanding and treatment microbial systems. This review examines various applications AI in microbiology, including activities such as predicting drug targets vaccine candidates, identifying microorganisms responsible for infectious diseases, classifying resistance antimicrobial drugs, disease outbreaks, well investigating interactions between microorganisms, quality assurance, Identification bacteria compliance with health standards. We summarized key algorithms Naive Bayes, Support Vector Machines, Deep Learning, Random Forests used microbiological studies. also address challenges criticisms associated microbiology. Finally, we discuss prospects AI, advances personalized medicine, reducing resistance, microbiome research, rapid diagnostics, environmental synthetic biology. Our includes a comprehensive analysis recent literature, evaluating research. systematic searches inclusion criteria ensure relevance reviewed Despite significant that brings data heterogeneity, model transparency, ethical considerations must be addressed. Interdisciplinary collaboration rigorous validation models are crucial overcome these challenges. future looks promising pathogen detection, monitoring. provides powerful tool revolutionize diagnosis, ecosystems.

Language: Английский

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A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 186, P. 109704 - 109704

Published: Jan. 26, 2025

Language: Английский

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A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites

Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 94, P. 106289 - 106289

Published: April 1, 2024

Malaria is a severe infectious disease caused by the Plasmodium parasite. The early and accurate detection of this crucial to reducing number deaths it causes. However, current method detecting malaria parasites involves manual examination blood smears, which time-consuming labor-intensive process, mainly performed skilled hematologists, especially in underdeveloped countries. To address problem, we have developed two deep learning-based systems, YOLO-SPAM YOLO-SPAM++, can detect responsible for at an stage. Our evaluation these systems using public datasets parasite images, MP-IDB IML, shows that they outperform state-of-the-art, with more than 11M fewer parameters baseline YOLOv5m6. YOLO-SPAM++ demonstrated substantial 10% improvement over up 20% against best-performing preliminary experiments conducted on Falciparum species MP-IDB. On other hand, showed slightly better results subsets without tiny parasites, while precision values 94%. Further cross-species generalization validations, merging training sets various within MP-IDB, consistently outperformed YOLOv5 across all species, emphasizing its superior performance parasites. These architectures be integrated into computer-aided diagnosis create reliable robust malaria.

Language: Английский

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Role of artificial intelligence in early diagnosis and treatment of infectious diseases

Infectious Diseases, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 26

Published: Nov. 14, 2024

Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as transformative force in healthcare, offering promising solutions to address this challenge. This review article provides comprehensive overview of the pivotal role AI can play treatment infectious diseases. It explores how AI-driven diagnostic tools, including machine learning algorithms, deep learning, image recognition systems, enhance accuracy efficiency disease detection surveillance. Furthermore, it delves into potential predict outbreaks, optimise strategies, personalise interventions based on individual patient data be used gear up drug discovery development (D3) process.The ethical considerations, challenges, limitations associated with integration management are also examined. By harnessing capabilities AI, healthcare systems significantly improve preparedness, responsiveness, outcomes battle against

Language: Английский

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AI in infectious diseases: The role of datasets

Drug Resistance Updates, Journal Year: 2024, Volume and Issue: 73, P. 101067 - 101067

Published: Feb. 10, 2024

Language: Английский

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VENet: Variational energy network for gland segmentation of pathological images and early gastric cancer diagnosis of whole slide images

Computer Methods and Programs in Biomedicine, Journal Year: 2024, Volume and Issue: 250, P. 108178 - 108178

Published: April 21, 2024

Language: Английский

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Digital pathology and artificial intelligence in renal cell carcinoma focusing on feature extraction: a literature review

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: Jan. 24, 2025

The integrated application of artificial intelligence (AI) and digital pathology (DP) technology has opened new avenues for advancements in oncology molecular pathology. Consequently, studies renal cell carcinoma (RCC) have emerged, highlighting potential histological subtype classification, aberration identification, outcome prediction by extracting high-throughput features. However, reviews these are still rare. To address this gap, we conducted a thorough literature review on DP AI applications RCC through database searches. Notably, found that models based deep learning achieved area under the curve (AUC) over 0.93 0.89-0.96 grading clear RCC, 0.70-0,89 prediction, 0.78 survival prediction. This finally discussed current state researches future directions.

Language: Английский

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Advancements in Digital Cytopathology Since COVID-19: Insights from a Narrative Review of Review Articles

Healthcare, Journal Year: 2025, Volume and Issue: 13(6), P. 657 - 657

Published: March 17, 2025

Background/Objectives: The integration of digitalization in cytopathology is an emerging field with transformative potential, aiming to enhance diagnostic precision and operational efficiency. This narrative review reviews (NRR) seeks identify prevailing themes, opportunities, challenges, recommendations related the process cytopathology. Methods: Utilizing a standardized checklist quality control procedures, this examines recent advancements future implications domain. Twenty-one studies were selected through systematic process. Results: results highlight key trends, digital First, study identifies pivotal themes that reflect ongoing technological transformation, guiding focus areas field. A major trend artificial intelligence (AI), which increasingly critical improving accuracy, streamlining workflows, assisting decision making. Notably, AI technologies like large language models (LLMs) chatbots are expected provide real-time support automate tasks, though concerns around ethics privacy must be addressed. also emphasize need for protocols, comprehensive training, rigorous validation ensure tools reliable effective across clinical settings. Lastly, holds significant potential improve healthcare accessibility, especially remote areas, by enabling faster, more efficient diagnoses fostering global collaboration telepathology. Conclusions: Overall, highlights impact cytopathology, efficiency, accessibility whole-slide imaging While plays role, broader on integrating solutions workflows collaboration. Addressing challenges such as standardization, ethical considerations crucial fully realize these advancements.

Language: Английский

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