Perspectives on AI use in medicine: views of the Italian Society of Artificial Intelligence in Medicine

The first annual meeting of the Italian Society for Artificial Intelligence in Medicine (Società Italiana Intelligenza Artificiale in Medicina, SIIAM) on December 7, 2023, marked a significant milestone in integrating artificial intelligence (AI) into Italy's healthcare framework. This paper reports on the collaborative workshop conducted during this event, highlighting the collective efforts of 51 professionals from diverse fields including medicine, engineering, data science, and law. The interdisciplinary nature of the participants played a crucial role in generating ideas for innovative AI solutions tailored to healthcare challenges.   Central to the discussions were several AI applications aimed at improving patient care and streamlining healthcare processes. Notably, the use of Large Language Models (LLMs) in remote monitoring of chronic patients emerged as an area of focus. These models promise enhanced patient monitoring through detailed symptom checking and anomaly detection, thereby facilitating timely medical interventions. Another significant proposal involved employing LLMs to improve empathy in medical communication, addressing the challenges posed by cultural diversity and high-stress levels among healthcare professionals.   Additionally, the development of Machine Learning algorithms for standardizing treatment in pediatric emergency departments was discussed, along with the need for educational initiatives to enhance AI adoption in rural healthcare settings. The workshop also explored using LLMs for efficient data extraction and analysis in scientific literature, interpreting healthcare norms, and streamlining Hospital Discharge Records.   These discussions underscored SIIAM's commitment to leveraging AI for healthcare innovation, setting a precedent for the future of healthcare in Italy. This paper provides a comprehensive overview of the ideas and solutions proposed at the workshop, reflecting the participants' forward-thinking vision and the potential of AI to revolutionize healthcare

Cyberbullismo 2.0: una ricerca qualitativa del fenomeno

Denso è il dibattito nel mondo scientifico su come l’uso delle tecnologie stia cambiando il modo di approcciarsi all’Altro delle nuove generazioni e di come si sta modificando il loro modus agendi della componente emotiva, sempre più contrassegnata dell’aggressività: il fenomeno del bullismo così come tutte le fenomenologie devianti, messe in atto da minori, destano infatti una preoccupazione crescente. A questa va aggiunta l’apprensione di molti genitori davanti al ‘ritiro sociale’, che sempre più minori adottano per isolarsi dal mondo reale e rifugiarsi in quello virtuale. Strettamente correlato al bullismo, il cyberbullismo consiste in reiterati atteggiamenti e comportamenti finalizzati ad offendere, spaventare, umiliare la vittima tramite mezzi elettronici. Necessaria, quindi si fa un’analisi delle peculiarità possedute dai comportamenti aggressivi online, elementi strettamente connessi alle caratteristica proprie del cyberspace, che possa rendere più preparati, coloro che sono chiamati ad educare

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

: Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. In this perspective article, we retrace the evolution of LLMs to understand the revolution brought by ChatGPT in the artificial intelligence (AI) field. The opportunities offered by LLMs in supporting scientific research are multiple and various models have already been tested in Natural Language Processing (NLP) tasks in this domain. The impact of ChatGPT has been huge for the general public and the research community, with many authors using the chatbot to write part of their articles and some papers even listing ChatGPT as an author. Alarming ethical and practical challenges emerge from the use of LLMs, particularly in the medical field for the potential impact on public health. Infodemic is a trending topic in public health and the ability of LLMs to rapidly produce vast amounts of text could leverage misinformation spread at an unprecedented scale, this could create an "AI-driven infodemic," a novel public health threat. Policies to contrast this phenomenon need to be rapidly elaborated, the inability to accurately detect artificial-intelligence-produced text is an unresolved issue

Vaccine hesitancy and knowledge regarding maternal immunization among reproductive age women in central Italy: a cross sectional study

background: vaccination in pregnancy offers protection to the mother and the newborn. In Italy, influenza, pertussis, and COVID-19 vaccinations are recommended in pregnancy, but vaccination coverage is still far from the national Immunization plan goals. we aimed to assess knowledge and attitude on maternal immunization in two groups of Italian women, in pregnancy and in reproductive age (non pregnant). methods: a cross sectional study on Italian childbearing age women gathering information on their knowledge on maternal immunization and attitudes to receiving influenza and pertussis vaccines in pregnancy was carried out at the university of rome tor vergata, between september 2019 and february 2020. logistic and multinomial regressions were chosen as statistical tests for our analysis. results: 1,031 women participated in the survey by answering the questionnaire. out of these, 553 (53.6%) women were pregnant, and 478 (46.4%) were in the reproductive age. 37% (204/553) of pregnant women and 41% (198/476) of non pregnant women are aware of the existence of an immunization plan for pregnant women in Italy. the group with age between 20 and 30, for both pregnant women and women in the reproductive age, has a better knowledge of vaccination in pregnancy. Working status is a variable associated with more awareness about vaccination during pregnancy only for pregnant women (OR = 2.34, p < 0.00001). educational status, trimester of pregnancy and knowledge on the topic are associated with vaccine hesitancy in our multivariate analysis for pregnant women. In the reproductive age group women who had a previous pregnancy are more likely to be hesitant towards vaccination in pregnancy, on the other hand the one with a higher knowledge and educational status are more likely to get vaccinated. conclusions: the study highlights the persistent vaccine hesitancy among Italian women of reproductive age and pregnant women. despite healthcare providers being identified as a reliable source of information, their recommendations alone are insufficient to overcome vaccine hesitancy. factors such as employment status, educational level, pregnancy trimester, and knowledge about vaccinations during pregnancy influence vaccine hesitancy. tailored educational interventions and communication campaigns targeting these areas can help reduce vaccine hesitancy and promote maternal immunization

Kynurenine/Tryptophan Ratio as a Potential Blood-Based Biomarker in Non-Small Cell Lung Cancer

The enzyme indoleamine 2,3-dioxygenase 1 (IDO1) degrade tryptophan (Trp) into kynurenine (Kyn) at the initial step of an enzymatic pathway affecting T cell proliferation. IDO1 is highly expressed in various cancer types and associated with poor prognosis. Nevertheless, the serum Kyn/Trp concentration ratio has been suggested as a marker of cancer-associated immune suppression. We measured Kyn and Trp in blood samples of a wide cohort of non-small-cell lung cancer (NSCLC) patients, before they underwent surgery, and analyzed possible correlations of the Kyn/Trp ratio with either IDO1 expression or clinical-pathological parameters. Low Kyn/Trp significantly correlated with low IDO1 expression and never-smoker patients; while high Kyn/Trp was significantly associated with older (>= 68 years) patients, advanced tumor stage, and squamous cell carcinoma (Sqcc), rather than the adenocarcinoma (Adc) histotype. Moreover, high Kyn/Trp was associated, among the Adc group, with higher tumor stages (II and III), and, among the Sqcc group, with a high density of tumor-infiltrating lymphocytes. A trend correlating the high Kyn/Trp ratio with the probability of recurrences from NSCLC was also found. In conclusion, high serum Kyn/Trp ratio, associated with clinical and histopathological parameters, may serve as a serum biomarker to optimize risk stratification and therapy of NSCLC patients

Autoimmune hepatitis with eosinophilic infiltration responsive to anti-interleukin-5 receptor treatment: a case report and literature review

Inflammatory tissue damage plays a role in the onset, progression, and exacerbation of various chronic autoimmune and metabolic diseases such as autoimmune hepatitis. Here we present a case of autoimmune hepatitis with liver eosinophilic infiltrate in a severe eosinophilic asthma patient who failed conventional immunosuppressive treatment and showed improvement in gastrointestinal symptoms after anti-interleukin-5 receptor treatment. Our case highlights the potential role of eosinophils in initiating or worsening liver inflammation in autoimmune liver disease. The link between eosinophilic inflammation, barrier damage, and chronic autoimmune diseases should be considered in clinical practice

Vaccine hesitancy and knowledge regarding maternal immunization among reproductive age women in central Italy: a cross sectional study

BackgroundVaccination in pregnancy offers protection to the mother and the newborn. In Italy, influenza, pertussis, and COVID-19 vaccinations are recommended in pregnancy, but vaccination coverage is still far from the National Immunization Plan goals. We aimed to assess knowledge and attitude on maternal immunization in two groups of Italian women, in pregnancy and in reproductive age (non pregnant).MethodsA cross sectional study on Italian childbearing age women gathering information on their knowledge on maternal immunization and attitudes to receiving influenza and pertussis vaccines in pregnancy was carried out at the University of Rome Tor Vergata, between September 2019 and February 2020. Logistic and multinomial regressions were chosen as statistical tests for our analysis.Results1,031 women participated in the survey by answering the questionnaire. Out of these, 553 (53.6%) women were pregnant, and 478 (46.4%) were in the reproductive age. 37% (204/553) of pregnant women and 41% (198/476) of non pregnant women are aware of the existence of an immunization plan for pregnant women in Italy. The group with age between 20 and 30, for both pregnant women and women in the reproductive age, has a better knowledge of vaccination in pregnancy. Working status is a variable associated with more awareness about vaccination during pregnancy only for pregnant women (OR = 2.34, p < 0.00001). Educational status, trimester of pregnancy and knowledge on the topic are associated with vaccine hesitancy in our multivariate analysis for pregnant women. In the reproductive age group women who had a previous pregnancy are more likely to be hesitant towards vaccination in pregnancy, on the other hand the one with a higher knowledge and educational status are more likely to get vaccinated.ConclusionsThe study highlights the persistent vaccine hesitancy among Italian women of reproductive age and pregnant women. Despite healthcare providers being identified as a reliable source of information, their recommendations alone are insufficient to overcome vaccine hesitancy. Factors such as employment status, educational level, pregnancy trimester, and knowledge about vaccinations during pregnancy influence vaccine hesitancy. Tailored educational interventions and communication campaigns targeting these areas can help reduce vaccine hesitancy and promote maternal immunization

Studio di parametri psicofisiologici su un campione di lavoratori esposti a stress lavoro correlato e sviluppo di scenari lavorativi in realtà virtuale immersiva per la simulazione del rischio da stress occupazionale

Il lavoro si inserisce nel progetto “Formazione qualificata e percorsi terapeutici multimediali in materia di patologie stress lavoro correlato” finanziato da INAIL e coordinato dalla UO. di Medicina Preventiva del Lavoro dell’AOUP con la collaborazione del Laboratorio PERCRO della Scuola Superiore Sant’Anna. Nel campione di lavoratori con Disturbo dell’Adattamento analizzato è stato osservato un maggiore livello di stress lavorativo nelle donne rispetto agli uomini (p=0.05) e una correlazione positiva fra PSM e SCL-90 (r=0.800 , p<0.001). Inoltre è stata rilevata una correlazione negativa tra cortisolo sierico e HF-HRV (r=-0.424, p=0.02) e una correlazione positiva tra cortisolo sierico e LF-HRV (r=0.424, p=0.02). Lo studio permette di ipotizzare un ruolo della Heart Rate Variability come strumento di sorveglianza dei lavoratori esposti a stress occupazionale. Al contempo la misura della Heart Rate Variability può essere integrata durante le sessioni in Realtà Virtuale per monitorare il grado di immersività. É stata progettata una piattaforma multiplayer immersiva in cui il paziente può interagire con lo psicologo/psicoterapeuta per il trattamento del Disturbo dell’Adattamento con la Terapia Cognitivo Comportamentale. Gli scenari lavorativi virtuali sono stati sviluppati in modo da massimizzare “plausibility illusion”, “place illusion” e “body”, minimizzando la richiesta di spazi e di personale. L’esperienza maturata durante il progetto potrebbe offrire un importante contributo alla metodologia per diagnosi eziologica delle malattie da stress lavoro-correlato della sfera psichica. Inoltre il progetto potrebbe indicare una nuova direzione per lo sviluppo di percorsi riabilitativi del lavoratore affetto da disabilità psichica e da malattia professionale da stress lavoro-correlato

A unified framework for uncertainty, compatibility analysis, and data fusion for multi-stereo 3-D shape estimation

This paper describes the uncertainty analysis performed for the reconstruction of a 3-D shape. Multiple stereo systems are employed to measure a 3-D surface with superimposed colored markers. The procedure comprised a detailed uncertainty analysis of all measurement phases, and the uncertainties evaluated were employed to perform a compatibility analysis of points acquired by different stereo pairs. The compatible acquired markers were statistically merged in order to obtain the measurement of a 3-D shape and an evaluation of the associated uncertainty. Both the compatibility analysis and the measurement merging are based on the evaluated uncertainty