Privacy-Preserving Deep Learning With Homomorphic Encryption: An Introduction

Privacy-preserving deep learning with homomorphic encryption (HE) is a novel and promising research area aimed at designing deep learning solutions that operate while guaranteeing the privacy of user data. Designing privacy-preserving deep learning solutions requires one to completely rethink and redesign deep learning models and algorithms to match the severe technological and algorithmic constraints of HE. This paper provides an introduction to this complex research area as well as a methodology for designing privacy-preserving convolutional neural networks (CNNs). This methodology was applied to the design of a privacy-preserving version of the well-known LeNet-1 CNN, which was successfully operated on two benchmark datasets for image classification. Furthermore, this paper details and comments on the research challenges and software resources available for privacy-preserving deep learning with HE

Tako-tsubo Syndrome as First Manifestation in a Case of Pheochromocytoma Developed From a Non-functional Adrenal Incidentaloma

Abstract Background: Pheochromocytoma is a catecholamine secreting tumor that, in extremely rare cases, may develop over time from a non-functional adrenal adenoma. Catecholamine excess can lead to a kind of cardiomyopathy similar to that seen in tako-tsubo syndrome (TTS). Case report: A 69 years old female with a history of type 2 diabetes, hypertension, and a non-functional right adrenal adenoma diagnosed 3 years earlier was referred to our center for further investigations. During the evaluation, she had a hypertensive crisis with chest pain, tachycardia, and diaphoresis. Suspecting an acute coronary syndrome, she underwent coronary angiography, which showed the typical features of TTS. The high 24 h-urinary metanephrines excretion and abdominal MRI findings were suggestive of pheochromocytoma. Right laparoscopic adrenalectomy was performed, with the resolution of all symptoms. Pathology findings confirmed the diagnosis of pheochromocytoma. After 12 months, the patient was still asymptomatic, with the echocardiography displaying a complete recovery of the left-ventricular function. Conclusions: The development of a pheochromocytoma from an adrenal non functional adenoma is an extremely rare event, but potentially life-threating because of the catecholamine-associated cardiovascular toxicity. In particular, TTS is a form of cardiomyopathy that has been increasingly described as associated with catecholamine-secreting tumors. The exclusion of pheochromocytoma in a patient with TTS has important therapeutic implications, since the administration of β-blockers may be extremely harmful in patients with catecholamine surge in the absence of adequate α-blockage. Keywords: adrenal incidentaloma; catecholamine; infarction; pheochromocytoma; tako-tsubo syndrome; ventricular dysfunction

Cancer specialist nurses’ perspectives of physical activity promotion and the potential role of physical activity apps in cancer care

Purpose: The purpose of this study was to understand breast, prostate and colorectal cancer Clinical Nurse Specialists’ (CNSs) perspectives on physical activity (PA) promotion and the role of smartphone apps to support PA promotion in cancer care. Methods: CNSs working in breast, prostate or colorectal cancer were recruited via advertisements distributed by professional organisations. In-depth semi-structured telephone interviews were conducted and analysed using thematic analysis. Results: 19 CNSs participated. The analysis resulted in 4 themes regarding CNSs’ perspectives of PA promotion within cancer care: i) policy changes in survivorship care have influenced CNSs’ promotion of PA; ii) CNSs recognise their role in supporting PA but sit within a wider system necessary for effective PA promotion; iii) CNSs use several techniques to promote PA within their consultations; iv) remaining challenges in PA promotion. The analysis resulted in 3 themes regarding CNSs’ perspectives on the use of apps to promote PA within cancer care: i) the influence of apps on access to PA support; ii) the role of apps in self-directed PA; iii) implementing apps in cancer care. Conclusions: The results of this study provide valuable insight into the CNS role and provide a number of important considerations for the development and implementation of PA interventions within cancer care, with a specific focus on smartphone-based interventions. Implications for cancer survivors: CNSs play an important role in PA promotion in cancer care and this research can inform the development of PA interventions delivered via smartphone app for people affected by cancer

Pain and Frailty in Hospitalized Older Adults

Introduction: Pain and frailty are prevalent conditions in the older population. Many chronic diseases are likely involved in their origin, and both have a negative impact on quality of life. However, few studies have analysed their association. Methods: In light of this knowledge gap, 3577 acutely hospitalized patients 65 years or older enrolled in the REPOSI register, an Italian network of internal medicine and geriatric hospital wards, were assessed to calculate the frailty index (FI). The impact of pain and some of its characteristics on the degree of frailty was evaluated using an ordinal logistic regression model after adjusting for age and gender. Results: The prevalence of pain was 24.7%, and among patients with pain, 42.9% was regarded as chronic pain. Chronic pain was associated with severe frailty (OR = 1.69, 95% CI 1.38–2.07). Somatic pain (OR = 1.59, 95% CI 1.23–2.07) and widespread pain (OR = 1.60, 95% CI 0.93–2.78) were associated with frailty. Osteoarthritis was the most common cause of chronic pain, diagnosed in 157 patients (33.5%). Polymyalgia, rheumatoid arthritis and other musculoskeletal diseases causing chronic pain were associated with a lower degree of frailty than osteoarthritis (OR = 0.49, 95%CI 0.28–0.85). Conclusions: Chronic and somatic pain negatively affect the degree of frailty. The duration and type of pain, as well as the underlying diseases associated with chronic pain, should be evaluated to improve the hospital management of frail older people

The multifaceted spectrum of liver cirrhosis in older hospitalised patients: Analysis of the REPOSI registry

Background: Knowledge on the main clinical and prognostic characteristics of older multimorbid subjects with liver cirrhosis (LC) admitted to acute medical wards is scarce. Objectives: To estimate the prevalence of LC among older patients admitted to acute medical wards and to assess the main clinical characteristics of LC along with its association with major clinical outcomes and to explore the possibility that well-distinguished phenotypic profiles of LC have classificatory and prognostic properties. Methods: A cohort of 6,193 older subjects hospitalised between 2010 and 2018 and included in the REPOSI registry was analysed. Results: LC was diagnosed in 315 patients (5%). LC was associated with rehospitalisation (age-sex adjusted hazard ratio, [aHR] 1.44; 95% CI, 1.10-1.88) and with mortality after discharge, independently of all confounders (multiple aHR, 2.1; 95% CI, 1.37-3.22), but not with in-hospital mortality and incident disability. Three main clinical phenotypes of LC patients were recognised: relatively fit subjects (FIT, N = 150), subjects characterised by poor social support (PSS, N = 89) and, finally, subjects with disability and multimorbidity (D&M, N = 76). PSS subjects had an increased incident disability (35% vs 13%, P < 0.05) compared to FIT. D&M patients had a higher mortality (in-hospital: 12% vs 3%/1%, P < 0.01; post-discharge: 41% vs 12%/15%, P < 0.01) and less rehospitalisation (10% vs 32%/34%, P < 0.01) compared to PSS and FIT. Conclusions: LC has a relatively low prevalence in older hospitalised subjects but, when present, accounts for worse post-discharge outcomes. Phenotypic analysis unravelled the heterogeneity of LC older population and the association of selected phenotypes with different clinical and prognostic features

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Privacy-preserving time series prediction with temporal convolutional neural networks

Designing and developing machine and deep learning solutions able to guarantee the privacy of users' data is a novel and promising research area. Homomorphic Encryption (HE) is playing a primary role in this area thanks to its ability to support the processing of machine and deep learning solutions directly on encrypted data. Currently, the research in this field focuses on HE-based machine and deep learning solutions for the processing of images and text, while the privacy-preserving processing of time series has been mostly left unattended due to the strong constraints imposed by HE on the machine and deep learning forecasting models. This paper introduces, for the first time in the literature, a general privacy-preserving solution for time series prediction based on HE and Temporal Convolutional Neural Networks. The novel content brought by the paper is twofold. From the algorithmic point of view, this paper introduces a family of Temporal Convolutional Neural Networks, called PINPOINT, which is integrated with a HE scheme to support the privacy-preserving time series prediction. From the technical point of view, this paper introduces and details a Cloud-based privacy-preserving system for the forecasting-as-a-service based on the proposed PINPOINT models. Experimental results on publicly available benchmarks show the effectiveness of the proposed solution for privacy-preserving time series prediction