This review focuses on the intersection of artificial intelligence and genomic data in cancer research. It explores the types of genomic data used in the literature, the methodologies of machine learning and deep learning, recent applications, and the challenges associated with this field. Through an analysis of 47,586 articles and addressing seven research questions, the study reveals significant growth in this area over the past years. While there has been remarkable progress, ongoing attention is needed to address ethical considerations, interpretability of algorithms, and potential data biases, to ensure the reliable and responsible use of these advanced technologies. Overall, this paper provides a comprehensive overview of the current research landscape, offering insights into both the potential and challenges of AI in genomic data research.

Despite the high impact of the COVID-19 pandemic on social interactions and healthcare workers’ (HWs’) mental health, few studies have investigated the association between social network characteristics and HWs’ mental health, particularly during the pandemic. Therefore, we aimed to assess the associations between public health residents’ (PHRs’) social network characteristics and depression. We used data from the Public Health Residents’ Anonymous Survey in Italy (PHRASI), a nationwide cross-sectional study. Social network characteristics were self-reported. Depressive symptoms were assessed using the nine-item Patient Health Questionnaire. Linear and logistic models adjusted for age, sex, physical activity, and alcohol were used. A moderation analysis by sex was also performed. A total of 379 PHRs participated in the survey (58% females, median age of 30 years). More peer-to-peer (odds ratio OR = 0.62 (0.47–0.83)) and supervisor support (OR = 0.49 (0.36–0.68)), more social participation ((OR) = 0.36 95% CI (0.25–0.50)), and having a partner (OR = 0.49 (0.25–0.96)) were significantly associated with a lower risk of clinically relevant depressive symptoms. Work-to-private-life interference was significantly associated with a higher risk of clinically relevant depressive symptoms (OR = 1.77 (1.28–2.45)). Promoting a supportive work environment and social participation as well as reducing work-to-private life interference can contribute to reducing the high burden among PHRs.

The COVID-19 pandemic has evolved into a severe psychosocial crisis affecting patients, their relatives, friends, and healthcare professionals. In Italy, public health residents (PHRs) remain essential to the national response to the pandemic. To assess their mental sphere, the “Public Mental Health” working group of the medical residents’ Assembly of the Italian Society of Hygiene and Preventive Medicine has designed the Public Health Residents’ Anonymous Survey in Italy (PHRASI). This is a nation-wide cross-sectional study based on an 88-item self-administered voluntary survey that evaluates how sociodemographic variables are associated with mental issues, including wellness, eating disorders, sleeplessness, alcohol misuse, depression, and anxiety. Data will be gathered by disseminating a Google Forms link across the Assembly network of medical residents. All PHRs enrolled in a four-year program in one of the Italian postgraduate schools of public health will be qualified as participants. PHRASI aims to draw a comprehensive and detailed picture of the mental health state of Italian PHRs. PHRs are a significant group of healthcare professionals that may serve as a future benchmark for developing and enacting regulations intended to support the mental health of healthcare professionals.

Depression is a widespread condition, which increased during the COVID-19 pandemic among healthcare workers as well. The large workload of the pandemic response also affected Public Health Residents (PHRs) who played an important role in infection prevention and control activities. This work aims to assess depression in Italian PHRs, based on data collected through the PHRASI (Public Health Residents’ Anonymous Survey in Italy) study. In 2022, 379 PHRs completed the self-administered questionnaire containing Patient Health Questionnaire-9 to evaluate clinically relevant depressive symptoms (PHQ-9 ≥ 10). Multivariate logistic regression shows that the intention (aOR = 3.925, 95% CI = (2.067–7.452)) and the uncertainty (aOR = 4.949, 95% CI = (1.872–13.086)) of repeating the test to enter another postgraduate school/general practitioner course and the simultaneous attendance of two traineeships (aOR = 1.832, 95% CI = (1.010–3.324)) are positively related with depressive symptoms. Conversely, the willingness to work in the current traineeship place (aOR = 0.456, 95% CI = (0.283–0.734)) emerged as a protective factor. Similar results were obtained considering mild-to-severe (PHQ-9 ≥ 5) depressive symptoms and/or stratifying by sex. The findings, suggesting the protective role of job satisfaction toward depression, might entail future interventions to improve the learning experience and promote work-life balance.

Unhealthy behaviors (UBs) can affect mental health. The most impactful of these are alcohol abuse, sedentary behavior, and sleep disturbances. Since these UBs are not well explored in medical residents, this study aims to overcome this gap, focusing on outcomes such as depression and anxiety. The Public Health Residents’ Anonymous Survey in Italy (PHRASI) is a nationwide cross-sectional study based on an 88-item questionnaire. UBs were explored through validated questionnaires: the Alcohol Use Disorders Identification Test-c (AUDIT-C), the International Physical Activity Questionnaire (IPAQ), and the Insomnia Severity Index (ISI). Depressive symptoms and anxiety were detected by Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), respectively. Hierarchical cluster analysis described clusters using responses from the AUDIT-C, IPAQ, and ISI. A total of 375 participants were included in this study. Three distinct clusters (CL) were identified: CL1 was characterized by a moderate risk for alcohol abuse and high insomnia dissatisfaction, with a significantly higher frequency of depressive symptoms (46%, p < 0.001) and anxiety (53%, p < 0.001); CL2 had no risk for alcohol abuse, high sleep satisfaction, and better mental health profile, with the lowest prevalence of depressive symptoms (15%, p < 0.001); CL3 had the highest risk of alcohol abuse, the highest rate of physical activity (40%, p = 0.013), and the lowest prevalence of anxiety (27%, p < 0.001). Subjects belonging to CL1 required much more attention to prevent the worsening of mental outcomes. Interventions for promoting mental health should be addressed in all Public Health schools to create more sustainable working conditions.