The Serums Tool-Chain:Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems

Digital technology is permeating all aspects of human society and life. This leads to humans becoming highly dependent on digital devices, including upon digital: assistance, intelligence, and decisions. A major concern of this digital dependence is the lack of human oversight or intervention in many of the ways humans use this technology. This dependence and reliance on digital technology raises concerns in how humans trust such systems, and how to ensure digital technology behaves appropriately. This works considers recent developments and projects that combine digital technology and artificial intelligence with human society. The focus is on critical scenarios where failure of digital technology can lead to significant harm or even death. We explore how to build trust for users of digital technology in such scenarios and considering many different challenges for digital technology. The approaches applied and proposed here address user trust along many dimensions and aim to build collaborative and empowering use of digital technologies in critical aspects of human society

Bleeding from ruptured hepatic metastases as a cause of syncope in an octogenarian: a case report

<p>Abstract</p> <p>Introduction</p> <p>Acute hemoperitoneum as a result of hemorrhage from liver metastases is an uncommon but serious condition. The use of appropriate imaging is important in the diagnosis and can have a profound impact on subsequent management. This case is important because the presentation was of recurrent syncopal episodes with an unusual underlying cause. This case highlights the need to consider this diagnosis in the differential in patients presenting with collapse in the acute setting.</p> <p>Case presentation</p> <p>We present the case of an 85-year-old Caucasian man who was admitted following a collapse episode and was found to be persistently hypotensive despite aggressive resuscitation. An acute intra-peritoneal bleed originating from hepatic metastases from an unknown primary was identified promptly with computed tomography imaging and was subsequently managed conservatively.</p> <p>Conclusions</p> <p>This case aims to convey key teaching points: (A) the need to consider intra-abdominal hemorrhage in the differential diagnosis when assessing patients with collapse; and (B) the use of appropriate imaging such as computed tomography can facilitate a prompt diagnosis and appropriate management steps can then be taken accordingly.</p

Collaborative Problem Solving using an Open Modeling Environment

This paper presents ModelsCreator version 3 (MC3) an environment that supports collaborative building of various kinds of models. MC3 is an environment that permits synchronous interaction of students at a distance who collaborate in building models out of primitive objects. The open character of MC3 means that students have access to an open set of primitive objects that can be used for building these models. A result of this characteristic is that the collaborating partners may reason using heterogeneous sets of primitive objects, in order to obtain a solution. In this paper we concentrate on the architecture of MC3 and the basic functionality of the environment. In particular we study the effect of the open character of the environment in collaboration and problem solving. Through experimentation it is demonstrated that the users of MC3 can have rich interaction in order to build or exchange at run time the necessary primitive objects for model building

A Comprehensive Survey of EEG Preprocessing Methods for Cognitive Load Assessment

Preprocessing electroencephalographic (EEG) signals during computer-mediated Cognitive Load tasks is crucial in Human-Computer Interaction (HCI). This process significantly influences subsequent EEG analysis and the efficacy of Artificial Intelligence (AI) models employed in Cognitive Load Assessment. Consequently, it stands as an indispensable procedure for developing dependable systems capable of adapting to users&#x2019; cognitive capacities and constraints. We systematically analyzed fifty-seven (57) research papers on computer-mediated Cognitive Load EEG experiments published between 2018 and 2023. The preprocessing methods identified were multiple, controversial, and strongly dependent on the particularities of each experiment and the derived experimental dataset. Our investigation involved the meticulous classification of preprocessing methods based on distinct parameters, namely the degree of user intervention, the noise level, and the subject pool size. Particular attention was paid to semi-automated denoising technology since conventional methods, advanced approaches, and standardized pipelines overwhelm research, but no optimum solution is available yet. This survey is anticipated to provide a valuable contribution to the rising demand for an efficient and fully automated preprocessing approach in EEG-based computerized Cognitive Load experiments

Providing assistance during decision-making problems solving in an educational modelling environment

In this paper we present the model-checking module of decision-making models in the frame of ModelsCreator, an educational modelling environment. The model-checking module aims to assist young students to construct qualitative models for decision-making problems solving. We specify the decision-making models that may be built and we explain the model checking mechanism. The model-checking mechanism compares the student model with the reference model constructed by the teacher and provides immediate advice to the student to help him create a valid model. So, the model-checking module of a decision-making model aims to facilitate student to structure convincing decisions in the proper situations. © 2009 International Federation for Information Processing