Deep learning and machine learning in CT-based COPD diagnosis: Systematic review and meta-analysis

International Journal of Medical Informatics, Journal Year: 2025, Volume and Issue: 196, P. 105812 - 105812

Published: Jan. 30, 2025

Language: Английский

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Early Diagnosis of Pneumonia and Chronic Obstructive Pulmonary Disease with a Smart Stethoscope with Cloud Server-Embedded Machine Learning in the Post-COVID-19 Era

Biomedicines, Journal Year: 2025, Volume and Issue: 13(2), P. 354 - 354

Published: Feb. 4, 2025

Background/Objectives: Respiratory diseases are common and result in high mortality, especially the elderly, with pneumonia chronic obstructive pulmonary disease (COPD). Auscultation of lung sounds using a stethoscope is crucial method for diagnosis, but it may require specialized training involvement pulmonologists. This study aims to assist medical professionals who non-pulmonologist doctors early screening COPD by developing smart cloud server-embedded machine learning diagnose sounds. Methods: The was developed Micro-Electro-Mechanical system (MEMS) microphone record mobile application then send them wirelessly server real-time classification. Results: model classifies into four categories: normal, pneumonia, COPD, other respiratory diseases. It achieved an accuracy 89%, sensitivity 89.75%, specificity 95%. In addition, testing healthy volunteers yielded 80% distinguishing normal diseased lungs. Moreover, performance comparison between two commercial auscultation stethoscopes showed comparable sound quality loudness results. Conclusions: holds great promise improving healthcare delivery post-COVID-19 era, offering probability most likely conditions diagnosis Its user-friendly design capabilities provide valuable resource delivering timely, evidence-based diagnoses, aiding treatment decisions, paving way more accessible care.

Language: Английский

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Assessing the Impact of New Technologies on Managing Chronic Respiratory Diseases

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(22), P. 6913 - 6913

Published: Nov. 16, 2024

Chronic respiratory diseases (CRDs), including asthma and chronic obstructive pulmonary disease (COPD), represent significant global health challenges, contributing to substantial morbidity mortality. As the prevalence of CRDs continues rise, particularly in low-income countries, there is a pressing need for more efficient personalized approaches diagnosis treatment. This article explores impact emerging technologies, artificial intelligence (AI), on management CRDs. AI applications, machine learning (ML), deep (DL), large language models (LLMs), are transforming landscape CRD care, enabling earlier diagnosis, treatment, enhanced remote patient monitoring. The integration with telehealth wearable technologies further supports proactive interventions improved outcomes. However, challenges remain, issues related data quality, algorithmic bias, ethical concerns such as privacy transparency. paper evaluates effectiveness, accessibility, implications AI-driven tools management, offering insights into their potential shape future healthcare. advanced managing like COPD holds enhancing early monitoring, though remain regarding considerations, regulatory oversight.

Language: Английский

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From prevention to management: exploring AI’s role in metabolic syndrome management: a comprehensive review

The Egyptian Journal of Internal Medicine, Journal Year: 2024, Volume and Issue: 36(1)

Published: Nov. 19, 2024

Abstract Background This review aims to comprehensively explore the integration of artificial intelligence (AI) in prevention, diagnosis, and treatment metabolic syndrome (MetS). MetS is characterized by a cluster conditions, posing growing public health threat globally. Recognizing limitations traditional management approaches, we emphasize potential AI transforming MetS, focusing on recent advancements applications risk prediction diagnosis. Body conclusion. The medicine expanding, particularly managing involving conditions like hypertension dyslipidemia. Diagnosis challenges stem from addressing multiple simultaneously. tools prove essential monitoring indices such as blood pressure glucose, identifying trends for adjustments. Lifestyle modifications are crucial, can facilitate these changes through user-friendly interfaces positive reinforcement. Standardization successful implementation medical practices necessary revolutionizing management, requiring focused future research efforts.

Language: Английский

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