Cochlear implant surgery is performed to restore hearing in patients with a range of hearing disorders. To optimise hearing outcomes, trauma during the insertion of a cochlear implant electrode has to be minimised. Factors that contribute to the degree of trauma caused during surgery include: the location of the electrode, type of electrode, and the competence level of the surgeon. Surgical competence depends on knowledge of anatomy and experience in a range of situations, along with technical skills.

The article is focused on modeling and simulation of pulmonary compartment behaving and response during gas flowing in the lungs. The pulmonary system model includes the two ways: derivation of mathematical model for individual parts respiratory system, and numerical simulation of these parts. Dynamical model behavior is based on the set of differential equations allowing for dynamical description of entire pulmonary compartment. These simulations are especially important for understanding pulmonary system during gas cycle, and also serve for prediction of behaving pulmonary diseases.

Epilepsy is a chronic neurological disorder characterized by recurrent, sudden discharges of cerebral neurons, called seizures. Seizures are not always clearly defined and have extremely varied morphologies. Neurophysiologists are not always able to discriminate seizures, especially in long-term EEG datasets. Affecting 1% of the world’s population with 1/3 of the epileptic patients not corresponding to anti-epileptic medication, epilepsy is constantly under the microscope and systems for automated detection of seizures are thoroughly examined.

A method for detection of Alzheimer's type dementia though analysis of vocalisation features that can be easily extracted from spontaneous speech is presented. Unlike existing approaches, this method does not rely on transcriptions of the patient's speech. Tests of the proposed method on a data set of spontaneous speech recordings of Alzheimer's patients (n=235) and elderly controls (n=242) show that accuracy of 68% can be achieved with a Bayesian classifier operating on features extracted through simple algorithms for voice activity detection and speech rate tracking.

"The user interface of the CDSS has not been well addressed by the field of research. In the previous study, we investigated the presentation of diagnostic output and proposed the hierarchical representation of differential diagnosis lists that provides an effective way of interfacing with a CDSS. To improve the input process, in this study, we proposed the incorporation of relevance feedback. Such feedback can be used to sharpen the search query, and to initiate a dialogue with the user, regarding the presence or absence of particular diagnostic information.

Though endoscope-based surgery is highly beneficial regarding the recovery of the patients, it may also raise difficult tasks during special surgical actions. The main disadvantage is the lack of the tactile information for the surgeon, who consequently has to rely on the visual information only. As a special scenario, some organs of the human body, like ureters and arteries, have similar visual appearances, so distinguishing them is very challenging in real-time endoscopic surgery in these days.

In an ongoing project aiming at a comprehensive AI-based tool to support clinical decisions in medical cancer therapy, the ontology OCTA is being developed. Its purpose is to provide general knowledge about active ingredients, therapy regimens, etc. that can be used by such a clinical decision support system. In this paper, we present a new extension of OCTA modelling co-medication and drug interactions, enabling the answering of queries relevant for medical decision making dealing with these aspects.

Post-traumatic emotional disorder event is a major cause of slow rehabilitation worldwide. The present study investigates the effects of emotional sound stimulation at different groups of subjects with TBI. At the base of our research strategy, we had used a group with diffuse axonal injury (DAI). We collected three groups of patients: 45 healthy adults, 20 patients with severe TBI and 19 patients with moderate TBI. Neurophysiology trials aim was to determine the processes that accompany emotional changes within traumatic brain damage.

Cardiac function is reduced after acute myocardial infarction due to myocardial injury and to changes in the viable non-ischemic myocardium, a process known as cardiac remodeling. Current treatment of patients with acute myocardial infarction (AMI) reduces infarct size, preserves left ventricular function, and improves survival. However, it does not prevent remodeling which leads to heart failure. The aim of the present study was to model the echocardiographically estimated data with respect to the surgically collected data using Neural Networks.

Segmentation of masses in mammography images is an important task in early detection of breast cancer. Although the quality of segmentation is crucial to avoid misdiagnosis, the segmentation process is a challenging task even for specialists, due to the presence of ill-defined edges and low contrast images. In this work, we propose an improvement on Random Walker algorithm to segment masses, by applying a fuzzy approach in the initialization stage. We evaluated the new approach compared with classical Random Walker, using 57 images of Mini-MIAS database.

Despite the widespread use of process models in healthcare organizations, there are many unresolved issues regarding the reading and comprehension of these models by domain experts. This is aggravated by the fact that there exists a plethora of process modeling languages for the graphical documentation of processes, whose use is often not consistent for various reasons. Hence, the identification of those factors fostering the comprehension of process models becomes crucial.

In order to improve medical processes in nephrology, we present an application that allows doctors to create biopsy protocols by using a digital pen on a tablet. The biopsy protocol app is seamlessly integrated into existing infrastructure at the hospital (see figure 1). Compared to other reporting tools, we provide (1) real-time hand-writing/gesture recognition and real-time feedback on the recognition results on the screen; (2) a real-time digitisation into structured data and PDF documents; and (3) the mapping of the transcribed contents into concepts of the Banff classification.

Malignant melanoma is one of the most rapidly increasing cancers globally and it is the most dangerous form of human skin cancer. Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma. Early detection of melanoma can be helpful and usually curable. Due to the difficulty for dermatologist’s in the interpretation of dermoscopy images, Computer Aided Diagnosis systems can be very helpful to facilitate the early detection. The automated detection of the lesion borders is one of the most important steps in dermoscopic image analysis.

As the stressed adolescents of today are the adults of tomorrow, it is important to prevent and diagnose early anxiety disorders and enhance overall self esteem and wellbeing of the youth. A novel intervention for Generalized Anxiety Disorders in adolescents is proposed, that incorporates current clinical guidelines and state-of-the art ICT technology.

Wearable devices are becoming an important interface between users and fitness activities. Their capabilities are improving exponentially and new strategies are being developed to track sports using sensors that are widely used in robotics. In combination with these wearable gadgets, smartphone applications are normally created to allow the user to visualise data, share data through social networks, or compete with other users. The technology behind these devices is often simple and uses sensors that can be found in a smartphone, such as GPS, accelerometer and gyroscope.

Comorbidities such as hypertension and lipid metabolism are often associated in diseases such as diabetes, and the early prediction of these is of great value when trying to manage progression. This is the start of a project to model multiple comorbidities in diabetes using dynamic Bayesian networks with latent variables in order to stratify patient cohorts. In this paper, we demonstrate some initial results on a dataset where the class imbalance problem poses an issue due to the rare occurrence of different individual comorbidities on a visit-by-visit basis.

In genome-wide association studies, genetic variants can be analyzed within statistical frameworks that take the underlying genetic model into consideration (e.g., the Cochran–Armitage test for trend or the logistic regression model). Should a researcher was to investigate the role played by the interaction between two or more genetic variants (epistasis), it would suffice to add interaction terms to a logistic regression model, where these terms correspond to the product of the genetic variants. However, such a model would not capture the subtlety of the interactions in the human genome.

INTRODUCTION: Adherence to physical activity might be the most important behavior associated with lower mortality and higher quality of life in cancer survivors. Presencial support groups are valuable and have been largely recommended, however, it may not be available for all patients. As an alternative, it is common that many women access Internet and social media resources looking for information, advice, and support in blogs, chat groups, Facebook, and Twitter.

In this paper we present a collaborative consultative knowledge system for cancer diseases. The «Worldwide Collaborative Consultative Knowledge System» aims to meet four goals. The first one is to be a tool which allows experts in a particular domain to develop a common knowledge base in a collaborative way. A second goal is the support of multiple knowledge bases. Each knowledge base is constructed to be used in a consultative way either from simple users or from experts of the domain offering high quality consultation services. In this paper we focus in cancer diseases.

"Introduction The increased prevalence of cancer survivors requires a focus on developing long-term, cost-effective management strategies to prevent and limit disability and morbidity. Background Cancer survivors with pain, weakness and restricted movement often benefit from targeted exercise programmes provided by a Physiotherapist. Physical, psychological and situational factors can impact on patients’ abilities to complete these exercises.

In the literature, PACS and Telemedicine are located in different or complementary works. However, when integrated as part of the same solution, both contribute to the healthcare process as a whole. This work describes the experience on integrating a PACS infrastructure to a statewide telemedicine system, allowing to the latter to benefit from concepts defined by the former in terms of acquisition, transmission and storage of digital images.