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Recenti progressi in medicina最新文献

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ClinEthix: supporto su aspetti etici e regolatori per la qualificazione di software utilizzati nella ricerca clinica. 临床研究软件资格认证的伦理和监管方面的支持。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45802
Sara Abbate, Maria Carmela Leo, Fabrizio Bianco, Diana Ferro, Alberto Eugenio Tozzi, Francesca Rocchi, Giuseppe Pontrelli
{"title":"ClinEthix: supporto su aspetti etici e regolatori per la qualificazione di software utilizzati nella ricerca clinica.","authors":"Sara Abbate, Maria Carmela Leo, Fabrizio Bianco, Diana Ferro, Alberto Eugenio Tozzi, Francesca Rocchi, Giuseppe Pontrelli","doi":"10.1701/4573.45802","DOIUrl":"https://doi.org/10.1701/4573.45802","url":null,"abstract":"<p><p>Clinical research is increasingly regulated. Despite growing artificial intelligence (AI) use in healthcare, there is a lack of adequate tools to support researchers in non profit (AI or not) studies. To assist with the classification of clinical software, ClinEthix, a prototype conversational tool, has been developed to help researchers with regulatory qualification. A survey of 20 researchers found it highly useful, clear and user-friendly. Future developments will integrate LLMs and human feedback to improve accuracy.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"615-616"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Intelligenza artificiale e medicina del sonno: valutazione comparativa di large language models sull’esame dell’Accademia Italiana di Medicina del Sonno con retrieval-augmented generation. 人工智能与睡眠医学:意大利睡眠医学学院考试中大型语言模型与retrieval-增强一代的比较评估。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45797
Edoardo Leo, Francesco Baglivo, Federico Starace, Andrea Romigi, Elena Antelmi, Caterina Rizzo, Ugo Faraguna
{"title":"Intelligenza artificiale e medicina del sonno: valutazione comparativa di large language models sull’esame dell’Accademia Italiana di Medicina del Sonno con retrieval-augmented generation.","authors":"Edoardo Leo, Francesco Baglivo, Federico Starace, Andrea Romigi, Elena Antelmi, Caterina Rizzo, Ugo Faraguna","doi":"10.1701/4573.45797","DOIUrl":"https://doi.org/10.1701/4573.45797","url":null,"abstract":"<p><p>Using Sleep Medicine guidelines and textbook, we evaluated four large language models (LLMs) (Llama 3.2 3B, Llama 3.3 70B, GPT 4o mini, Gemini 2.0 Flash) on AIMS certification questions, comparing baseline and Retrieval Augmented Generation (RAG) performance. RAG improved accuracy in all models (e.g., Llama 3.2 +9.6 points, Gemini 2.0 +4.0 points), highlighting RAG's role in enhancing LLM reliability in specialized medical domain.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"605-606"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sorveglianza delle infezioni del sito chirurgico tramite applicazione di natural language processing su lettere di dimissione ospedaliera: studio retrospettivo presso un ospedale universitario. 在医院出院单上使用自然语言处理来监测手术部位的感染:在教学医院进行回访研究。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45800
Nunzio Zotti, Guglielmo Arzilli, Francesco Baglivo, Luigi De Angelis, Andrea Porretta, Caterina Rizzo
{"title":"Sorveglianza delle infezioni del sito chirurgico tramite applicazione di natural language processing su lettere di dimissione ospedaliera: studio retrospettivo presso un ospedale universitario.","authors":"Nunzio Zotti, Guglielmo Arzilli, Francesco Baglivo, Luigi De Angelis, Andrea Porretta, Caterina Rizzo","doi":"10.1701/4573.45800","DOIUrl":"https://doi.org/10.1701/4573.45800","url":null,"abstract":"<p><p>An AI system based on NLP and machine learning has been developed to identify surgical site infections (SSIs) from hospital discharge letters. After advanced pre-processing and imbalance handling, BERT-FT achieved the best performance (F1=0.79), outperforming TF-IDF and W2V. Large language models (LLMs) showed limitations. The system could support semi-automatic SSI surveillance, with prospects for optimisation in translations, prompts, and infrastructure.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"611-612"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Migliorare l’assistenza per la salute mentale con la fenotipizzazione digitale: raggruppamento dei comportamentit dei pazienti per il supporto decisionale personalizzato. 通过数字表型来改善心理健康:将患者行为分组，以支持个性化决策。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45778
Joy Bordini, Rita Cosoli
{"title":"Migliorare l’assistenza per la salute mentale con la fenotipizzazione digitale: raggruppamento dei comportamentit dei pazienti per il supporto decisionale personalizzato.","authors":"Joy Bordini, Rita Cosoli","doi":"10.1701/4573.45778","DOIUrl":"https://doi.org/10.1701/4573.45778","url":null,"abstract":"<p><p>Breakthrough digital phenotyping approach reveals three distinct behavioral patterns from smartphone data that could revolutionize personalized mental health care. Using AI clustering on 77 users, we discovered \"Night Owls\", \"Routine-Oriented\", and \"Always-Connected\" behavioral types with 90%+ accuracy. Our explainable ML pipeline identifies key digital biomarkers for targeted interventions, offering clinicians data-driven insights for precision psychiatry.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"567-568"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predizione del tipo di mutazione nelle malattie mitocondriali primarie tramite modelli di machine learning applicati a dati clinici non genetici né istologici. 利用应用于临床非遗传或组织学数据的机器学习模型预测初级线粒体疾病的突变类型。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45801
Sara Mazzucato, Piervito Lopriore, Francesco Daddoveri, Costanza Lamperti, Valerio Carelli, Olimpia Musumeci, Serenella Servidei, Silvestro Micera, Michelangelo Mancuso, Andrea Bandini
{"title":"Predizione del tipo di mutazione nelle malattie mitocondriali primarie tramite modelli di machine learning applicati a dati clinici non genetici né istologici.","authors":"Sara Mazzucato, Piervito Lopriore, Francesco Daddoveri, Costanza Lamperti, Valerio Carelli, Olimpia Musumeci, Serenella Servidei, Silvestro Micera, Michelangelo Mancuso, Andrea Bandini","doi":"10.1701/4573.45801","DOIUrl":"https://doi.org/10.1701/4573.45801","url":null,"abstract":"<p><p>This study shows that machine learning can accurately distinguish between mitochondrial and nuclear DNA mutations in primary mitochondrial diseases using only non-genetic and non-histological clinical data. While language models underperform in comparison, they show potential as complementary diagnostic tools.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"613-614"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GLARE-Edu: una piattaforma IA per la formazione personalizzata e il supporto decisionale nell’applicazione delle linee guida cliniche. glar - edu:在应用临床指导方针时提供个性化培训和决策支持的IA平台。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45784
Annalisa Roveta, Luigi Mario Castello, Francesca Ugo, Marco Petronio, Paolo Terenziani, Alessio Bottrighi, Erica Raina, Antonio Maconi
{"title":"GLARE-Edu: una piattaforma IA per la formazione personalizzata e il supporto decisionale nell’applicazione delle linee guida cliniche.","authors":"Annalisa Roveta, Luigi Mario Castello, Francesca Ugo, Marco Petronio, Paolo Terenziani, Alessio Bottrighi, Erica Raina, Antonio Maconi","doi":"10.1701/4573.45784","DOIUrl":"https://doi.org/10.1701/4573.45784","url":null,"abstract":"<p><p>GLARE-Edu is an AI-powered, adaptive platform supporting healthcare professionals and students in learning clinical guidelines and improving decision-making through personalized training and realistic case simulations. Two case studies demonstrated significant improvements in guideline application and user satisfaction.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"579-580"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Implementazione e validazione di una pipeline RAG-based per l’automazione delle indagini epidemiologiche: analisi di performance e applicabilità nel contesto dei sistemi di sorveglianza sanitaria italiana. 流行病学调查自动化ragp - line的实施和验证:绩效分析和意大利卫生监测系统的适用性。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45799
Giuseppe Vella, Francesca Sala, Vincenzo Pisciotta, Concetta Anzalone
{"title":"Implementazione e validazione di una pipeline RAG-based per l’automazione delle indagini epidemiologiche: analisi di performance e applicabilità nel contesto dei sistemi di sorveglianza sanitaria italiana.","authors":"Giuseppe Vella, Francesca Sala, Vincenzo Pisciotta, Concetta Anzalone","doi":"10.1701/4573.45799","DOIUrl":"https://doi.org/10.1701/4573.45799","url":null,"abstract":"<p><p>We implemented a three-phase AI pipeline for automating epidemiological investigations: structured PDF data extraction, RAG-driven report generation, and final document assembly. Expert validation (n=200) yielded high scores for completeness (4.7), accuracy (4.5), relevance (4.6), clarity (4.8), and timeliness (4.4), with inter-rater κ=0.85 and a 60% time reduction. The system is scalable to serve other surveillance systems.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"609-610"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
[From malnutrition to surgery: the role of supportive parenteral nutrition.] 【从营养不良到手术：支持性肠外营养的作用】
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45806
Lidia Santarpia
{"title":"[From malnutrition to surgery: the role of supportive parenteral nutrition.]","authors":"Lidia Santarpia","doi":"10.1701/4573.45806","DOIUrl":"https://doi.org/10.1701/4573.45806","url":null,"abstract":"<p><p>Patients with pancreatic cancer frequently present with protein-energy malnutrition, which can negatively affect prognosis and treatment tolerance. We report the clinical case of a 55-year-old man with locally advanced pancreatic adenocarcinoma, deemed unresectable at diagnosis, who experienced severe weight loss (-23 kg in the last 4 months) and marked clinical deterioration. The prescription of supportive parenteral nutrition (PN) allowed stabilization of body weight, improvement of fatigue, and the resumption of chemotherapy cycles that had previously been interrupted due to worsening clinical conditions. After eight cycles of chemotherapy, restaging imaging revealed tumour regression, making a surgical reassessment possible. This case highlights the importance of early nutritional screening and targeted nutritional intervention in oncology patients, in order to optimize ongoing treatment response and broaden therapeutic opportunities.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"e67-e69"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Intelligenza artificiale e IoT per l’ottimizzazione dei tempi in sala operatoria: un confronto tra un modello generale e un modello chirurgia specifico. 人工智能和IoT用于优化手术室时间:通用模型和特定手术模型的比较。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45782
Valentina Bellini, Matteo Panizzi, Tania Domenichetti, Matteo Guarnieri, Elena Bignami
{"title":"Intelligenza artificiale e IoT per l’ottimizzazione dei tempi in sala operatoria: un confronto tra un modello generale e un modello chirurgia specifico.","authors":"Valentina Bellini, Matteo Panizzi, Tania Domenichetti, Matteo Guarnieri, Elena Bignami","doi":"10.1701/4573.45782","DOIUrl":"https://doi.org/10.1701/4573.45782","url":null,"abstract":"<p><p>The combined use of IoT and AI enables automatic and precise collection of operative times through BLE bracelets, improving efficiency compared to manual recording. Surgery-specific models, trained on real data, better predict procedure duration, optimizing management and resources in the operating room.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"575-576"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Towards learning healthcare systems in Italy: opportunities and challenges of AI at point-of-care. 在意大利学习医疗保健系统：人工智能在护理点的机遇和挑战。
Recenti progressi in medicina Pub Date : 2025-10-01 DOI: 10.1701/4573.45776
Luigi De Angelis, Alessio Pivetta, Francesco Baglivo, Luca Alessandro Cappellini, Francesca Aurora Sacchi, Marcello Di Pumpo, Mattia Mercier, Giacomo Diedenhofen, Mattia Di Bartolomeo, Francesco Andrea Causio, Alessandro Belpiede, Alberto Eugenio Tozzi, Diana Ferro
{"title":"Towards learning healthcare systems in Italy: opportunities and challenges of AI at point-of-care.","authors":"Luigi De Angelis, Alessio Pivetta, Francesco Baglivo, Luca Alessandro Cappellini, Francesca Aurora Sacchi, Marcello Di Pumpo, Mattia Mercier, Giacomo Diedenhofen, Mattia Di Bartolomeo, Francesco Andrea Causio, Alessandro Belpiede, Alberto Eugenio Tozzi, Diana Ferro","doi":"10.1701/4573.45776","DOIUrl":"https://doi.org/10.1701/4573.45776","url":null,"abstract":"<p><p>In Italy, the growing enthusiasm for artificial intelligence (AI) in healthcare contrasts with significant infrastructural, cultural, and trust-related barriers hindering its real-world adoption. Moving beyond the hype requires a systems thinking approach, proposing the learning health system (LHS) framework as a structured path for integration. We highlight the complementary roles of AI models: traditional machine learning (ML) is proven for diagnostics and prognostics, while large language models (LLMs) excel at administrative tasks and can structure unstructured data to train robust ML tools. The LHS cycle reveals key challenges for Italy: moving from Practice-to-Data requires overcoming data fragmentation; from Data-to-Knowledge involves transforming data into insights while mitigating bias; and from Knowledge-to-Practice necessitates bridging the gap between evidence and clinical workflow by building trust and AI literacy. Ultimately, successful and equitable AI implementation depends on a holistic strategy combining infrastructure development, multidisciplinary collaboration, and robust governance to enhance the quality and sustainability of the national healthcare system.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":"116 10","pages":"556-560"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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