Venet Osmani

Venet Osmani
Fondazione Bruno Kessler | FBK

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87
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Publications

Publications (87)
Article
Full-text available
Introduction Delirium occurrence is common and preventive strategies are resource intensive. Screening tools can prioritize patients at risk. Using machine learning, we can capture time and treatment effects that pose a challenge to delirium prediction. We aim to develop a delirium prediction model that can be used as a screening tool. Methods Fro...
Article
Full-text available
Introduction: Intoxications are common in intensive care units (ICUs). The number of causative substances is large, mortality usually low. This retrospective cohort study aims to characterize differences of intoxicated compared to general ICU patients, point out variations according to causative agents, as well as to highlight differences between...
Preprint
A bstract Background racial bias has been shown to be present in clinical data, affecting patients unfairly based on their race, ethnicity and socio-economic status. This problem has the potential to be significantly exacerbated in the light of Artificial Intelligence-aided clinical decision making. We sought to investigate whether bias can be int...
Article
Full-text available
Background: Mortality in sepsis remains high. Studies in small cohorts have shown that red cell distribution width (RDW) is associated with mortality. The aim of this study was to validate these findings in a large multi-centre cohort. Methods: We conducted this retrospective analysis of the multi-center eICU Collaborative Research Database in 1...
Article
Background: The SARS-CoV-2 coronavirus disease (COVID-19) pandemic is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. Objective: This study aimed to evaluate machine-learning based prognostication models for critically ill elderly COVID...
Conference Paper
Full-text available
An important target for machine learning research is obtaining unbiased results, which require addressing bias that might be present in the data as well as the methodology. This is of utmost importance in medical applications of machine learning, where trained models should be unbiased so as to result in systems that are widely applicable, reliable...
Article
Full-text available
Screening for colorectal cancer (CRC) continues to rely on colonoscopy and/or fecal occult blood testing since other (non-invasive) risk-stratification systems have not yet been implemented into European guidelines. In this study, we evaluate the potential of machine learning (ML) methods to predict advanced adenomas (AAs) in 5862 individuals parti...
Article
Full-text available
Background Higher survival has been shown for overweight septic patients compared with normal or underweight patients in the past. This study aimed at investigating the management and outcome of septic ICU patients in different body mass index (BMI) categories in a large multicenter database. Methods In total, 16,612 patients of the eICU collabora...
Preprint
Full-text available
An important target for machine learning research is obtaining unbiased results, which require addressing bias that might be present in the data as well as the methodology. This is of utmost importance in medical applications of machine learning, where trained models should be unbiased so as to result in systems that are widely applicable, reliable...
Preprint
BACKGROUND The COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. OBJECTIVE The aim of this study was to evaluate machine learning–based prognostication models for critically ill elderly COVID-19 pat...
Article
Elevations in initially obtained serum lactate levels are strong predictors of mortality in critically ill patients. Identifying patients whose serum lactate levels are more likely to increase can alert physicians to intensify care and guide them in the frequency of tending the blood test. We investigate whether machine learning models can predict...
Article
Stress assessment is a complex issue and numerous studies have examined factors that influence stress in working environments. Research studies have shown that monitoring individuals' behaviour parameters during daily life can also help assess stress levels. In this study, we examine assessment of work-related stress using features derived from sen...
Article
Full-text available
Wastewater treatment plants use many sensors to control energy consumption and discharge quality. These sensors produce a vast amount of data which can be efficiently monitored by automatic systems. Consequently, several different statistical and learning methods are proposed in the literature which can automatically detect faults. While these meth...
Preprint
Full-text available
Blood lactate concentration is a strong indicator of mortality risk in critically ill patients. While frequent lactate measurements are necessary to assess patient's health state, the measurement is an invasive procedure that can increase risk of hospital-acquired infections. For this reason we formally define the problem of lactate prediction as a...
Preprint
Full-text available
Progress of machine learning in critical care has been difficult to track, in part due to absence of public benchmarks. Other fields of research (such as vision and NLP) have already established various competitions and benchmarks, whereas only recent availability of large clinical datasets has enabled the possibility of public benchmarks. Taking a...
Preprint
Full-text available
Of the 2652 articles considered, 106 met the inclusion criteria. Review of the included papers resulted in identification of 43 chronic diseases, which were then further classified into 10 disease categories using ICD-10. The majority of studies focused on diseases of the circulatory system (n=38) while endocrine and metabolic diseases were fewest...
Article
Full-text available
Evaluation of dressing activities is essential in the assessment of the performance of patients with psycho-motor impairments. However, the current practice of monitoring dressing activity (performed by the patients in front of the therapist) has a number of disadvantages when considering the personal nature of dressing activity as well as inconsis...
Article
Full-text available
Background: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the secondary use of electronic health records (EHRs), where patient data are analyzed to conduct clinical and translati...
Preprint
BACKGROUND Worldwide, the burden of chronic diseases is growing, necessitating novel approaches that complement and go beyond evidence-based medicine. In this respect a promising avenue is the secondary use of Electronic Health Records (EHR) data, where clinical data are analysed to conduct basic and clinical and translational research. Methods bas...
Conference Paper
Background. Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of healthcare data is beginning to revolutionize healthcare. Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) a...
Article
Full-text available
Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of healthcare data is beginning to revolutionize healthcare. Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) and data gene...
Article
Full-text available
Explosion of number of smartphone apps and their diversity has created a fertile ground to study behaviour of smartphone users. Patterns of app usage, specifically types of apps and their duration are influenced by the state of the user and this information can be correlated with the self-reported state of the users. The work in this paper is along...
Chapter
Motor activity in physical and psychological stress exposure has been studied almost exclusively with self-assessment questionnaires and from reports that derive from human observer, such as verbal rating and simple descriptive scales. However, these methods are limited in objectively quantifying typical behaviour of stress. We propose to use accel...
Article
Full-text available
We describe an innovative framework for prescription of personalised health apps by integrating Personal Health Records (PHR) with disease-specific mobile applications for managing medical conditions and the communication with clinical professionals. The prescribed apps record multiple variables including medical history enriched with innovative fe...
Conference Paper
Electronic Health Records (EHR) have been one of the factors in transforming healthcare and health management by providing electronic access to information recorded on paper charts. However, increasing interest of patients to be actively involved in the management of their condition and their health has necessitated evolution of EHRs so as to accom...
Conference Paper
We describe an innovative framework for prescription of personalised health apps by integrating Personal Health Records (PHR) with disease-specific mobile applications for managing medical conditions and the communication with clinical professionals. The prescribed apps record multiple variables including medical history enriched with innovative fe...
Article
Objective: Stress at work is a significant occupational health concern. Recent studies have used various sensing modalities to model stress behaviour based on non-obtrusive data obtained from smartphones. However, when the data for a subject is scarce it becomes a challenge to obtain a good model. Methods: We propose an approach based on a combi...
Article
Increase in workload across many organisations and consequent increase in occupational stress is negatively affecting the health of the workforce. Measuring stress and other human psychological dynamics is difficult due to subjective nature of selfreporting and variability between and within individuals. With the advent of smartphones it is now pos...
Article
There is growing amount of scientific evidence that motor activity is the most consistent indicator of bipolar disorder. Motor activity includes several areas such as body movement, motor response time, level of psychomotor activity, and speech related motor activity. Studies of motor activity in bipolar disorder have typically used self-reported q...
Conference Paper
Full-text available
Stress at work is a significant occupational health concern nowadays. Thus, researchers are looking to find comprehensive approaches for improving wellness interventions relevant to stress. Recent studies have been conducted for inferring stress in labour settings; they model stress behaviour based on non-obtrusive data obtained from smartphones. H...
Conference Paper
hile moderate exposure to stress at work can act as productivity booster, prolonged exposure not only decreases productivity, but it can also lead to an array of health related problems. Therefore, monitoring stress levels and more importantly correlated stressors, becomes prerequisite for a productive workforce. Considering that verbal interaction...
Article
Full-text available
An observational study with patients diagnosed with bipolar disorder investigates whether data from smartphone sensors can be used to recognize bipolar disorder episodes and detect behavior changes that can signal an onset of an episode using objective data.
Conference Paper
Explosion of number of smartphone apps and their diversity has created a fertile ground to study behaviour of smartphone users. Patterns of app usage, specifically types of apps and their duration are influenced by the state of the user and this information can be correlated with the self-reported state of the users. The work in this paper is along...
Article
Full-text available
Capabilities of smartphones can be utilised to monitor a range of aspects of users' behaviour. This has potential to affect a number of areas where users' behaviour is considered relevant information. Most notably, healthcare in general and mental health in particular are excellent candidates to utilise capabilities of smartphones, since mental dis...
Conference Paper
Full-text available
Social interactions play an important role in the overall well-being. Current practice of monitoring social interactions through questionnaires and surveys is inadequate due to recall bias, memory dependence and high end-user effort. However, sensing capabilities of smart-phones can play a significant role in automatic detection of social interacti...
Article
This paper proposes using mobile technologies to provide an insight into social context at workplace. It provides takeaways for extracting features that are relevant for interpreting social context and types of social interactions, formal or informal. Our approach uses mobile phones and accelerometers to detect interpersonal spatial and speech rela...
Conference Paper
Telecommunication networks currently follow the reactive approach; that is, network conditions change based on current behaviour of users and state of network resources. However, network efficiency and resource optimization can increase manifold, if the networks had the capability to anticipate behaviour of users and their network utilization. This...
Article
Full-text available
Today's health care is difficult to imagine without the possibility to objectively measure various physiological parameters related to patients symptoms (from temperature through blood pressure to complex tomographic procedures). Psychiatric care remains a notable exception that heavily relies on patient interviews and self assessment. This is due...
Conference Paper
Bipolar Disorder is a disease that is manifested with cycling periods of polar episodes, namely mania and depression. Depressive episodes are manifested through disturbed mood, psychomotor retardation, behaviour change, decrease in energy levels and length of sleep. Manic episodes are manifested through elevated mood, psychomotor acceleration and i...
Conference Paper
Full-text available
In this paper we demonstrate how smart phone sensors, specifically acceleration sensor and GPS traces, can be used as an objective “measurement device” for aiding psychiatric diagnosis. In a trial with 12 bipolar disorder patients con- ducted over a total (summed over all patients) of over 1000 days (on average 12 weeks per patient) we have achieve...
Article
Full-text available
Mental disorders can have a significant, nega-tive impact on sufferers' lives, as well as on their friends and family, healthcare systems and other parts of society. Approximately 25 % of all people in Europe and the USA experience a mental disorder at least once in their lifetime. Currently, monitoring mental disorders relies on subjective clinica...
Article
Full-text available
This paper presents a series of challenges for developing mobile health solutions for mental health as a result of MONARCA project three-year activities. The lessons learnt on the design, development and evaluation of a mobile health system for supporting the treatment of bipolar disorder. The findings presented here are the result of over 3 years...
Article
This paper presents a series of challenges for developing mobile health solutions for mental health as a result of MONARCA project three-year activities. The lessons learnt on the design, development and evaluation of a mobile health system for supporting the treatment of bipolar disorder. The findings presented here are the result of over 3 years...
Article
This paper presents a series of reflections on the use of experiences gained in ubiquitous computing research to define their potential exploitation in the field of networking. On this regard, this paper presents preliminary ideas aiming at defining the concept of Human Aware Networking (HAN). The main idea behind HAN is to utilize the sensed conte...
Article
Full-text available
In this paper, we demonstrate how smart-phone sensors, specifically inertial sensors, and GPS traces, can be used as an objective “measurement device” for aiding psychiatric diagnosis. In a trial with 12 bipolar disorder patients conducted over a total (summed over all patients) of over 1000 days (on average 12 weeks per patient) we have achieved...
Conference Paper
Full-text available
Mobile computing is changing the landscape of clinical monitoring and self-monitoring. One of the major impacts will be in healthcare, where increase in number of sensing modalities is providing more and more information on the state of overall wellbeing, behaviour and health. There are numerous applications of mobile computing that range from well...
Conference Paper
Full-text available
In this paper, we present the concept of grouping individuals and detecting their proximity by emitting/receiving inaudible tones using their mobile phones. The inspiration stems from uniforms metaphor (of different colors) that groups subjects based on the roles, occupations or teams. The goal is to get an insight into the social context and socia...
Article
Full-text available
Localization plays an essential role in many ubiquitous computing applications. While the outdoor location-aware services based on GPS are becoming increasingly popular, their proliferation to indoor environments is limited due to the lack of widely available indoor localization systems. The de-facto standard for indoor positioning is based on Wi-F...
Article
Full-text available
Social interaction is one of the basic components of human life that impacts thoughts, emotions, decisions, and the overall wellbeing of individuals. In this regard, monitoring social activity constitutes an important factor in a number of disciplines, particularly those related to social and health sciences. Sensor-based social interaction data co...
Article
Full-text available
In the area of human behaviour analysis, smartphones are opening new possibilities where a multitude of embedded sensors can be used to regularly monitor users’ daily activities and interactions in a non-obtrusive way. In this paper we focus on proximity detection, which refers to the ability of a system to recognize the co-location of two or more...
Article
Full-text available
This Theme issue focuses on the emerging research of ubiquitous technologies to support mental health. So far, the majority of work presented in the field of ubiquitous healthcare has focused on supporting people affected by somatic diseases. However, increasing number of diseases affecting mental health has prompted research on technologies to sup...
Chapter
The association between social relationships and psychological health has been established fairly recently, in the last 30-40 years, relying on survey-based methods to record past activities and the psychological responses in individuals. However, using the self-reporting methods for capturing social behavior exhibits a number of shortcomings inclu...
Article
Full-text available
Equipment of mobile phones with various kinds of sensors is transforming these devices from mere capabilities of voice and internet access to devices capable of sensing a number of phenomena pertaining to their users. In this paper we make use of these capabilities of phones to detect social interactions between people and analyze social context by...
Article
Full-text available
The level of social activity is linked to the overall wellbeing and to various disorders, including stress. In this regard, a myriad of automatic solutions for monitoring social interactions have been proposed, usually including audio data analysis. Such approaches often face legal and ethical issues and they may also raise privacy concerns in moni...
Article
Full-text available
Mobile devices are increasingly becoming a proxy to habits and daily patterns of users. This is opening new possibilities in the area of human behaviour analysis, where the many sensors available on smartphones can be used to regularly monitor users' daily activities and interactions in an non-obtrusive way. In this paper we focus on proximity dete...
Conference Paper
Full-text available
Emerging studies suggest that sedentary work style is often associated with deleterious physiological implications, including diabetes, high blood pressure and obesity. However, only few studies linked prolonged periods of sitting with psychological responses thus the implications of sedentary behavior on mental health still remain highly unexplore...
Conference Paper
Full-text available
The level of participation in social interactions has been shown to have an impact on various health outcomes, while it also reflects the overall wellbeing status. In health sciences the standard practice for measuring the amount of social activity relies on periodical self-reports that suffer from memory dependence, recall bias and the current moo...
Conference Paper
Full-text available
This paper describes a stress treatment platform developed as part of the Interstress project. The platform includes multimodal mobile sensing which serves as an input to guide interactive relaxation exercises. The prototype application is described along with its main functionality.
Article
Sedentary behaviour is considered to be a major factor impacting a number of health outcomes while use of technology in the workplace is increasingly contributing to the amount of sedentary time. Even if guidelines on the amount of physical activity are followed outside of workplace, sedentary work style still has a deleterious impact on health. Th...
Conference Paper
Full-text available
Typical localization systems use various features of the signal to estimate the distance, including received signal strength indicator (RSSI), timing information or angle of arrival (AoA). However, there are a number of signal features of FM radio that may also be suitable for localization, namely stereo channel separation (SCS) and signal to noise...
Article
Full-text available
Monitoring and evaluation of Activities of Daily Living in general, and dressing activity in particular, is an important indicator in the evaluation of the overall cognitive state of patients. In addition, the effectiveness of therapy in patients with motor impairments caused by a stroke, for example, can be measured through long-term monitoring of...
Conference Paper
RFID technology has proven to be an effective solution in many applications for monitoring demented patients. However, its wider acceptance is still limited by prohibitive deployment costs, technological limitations and privacy concerns. In this paper, an RFID-based indoor tracking system was analyzed regarding an additional barrier of RFID's accep...