The Internet has grown into a world of its own, and its ethereal space now offers capabilities that could aid physicians in their duties in numerous ways. In recent years software functions have moved from the individual's local hardware to a central server that operates from a remote location. This centralization is called cloud computing. Privacy laws that speak to the protection of patient confidentiality are complex and often difficult to understand in the context of an ever-growing cloud-based technology. This article is a review of the legal background of protected health records, as well as cloud technology and physician applications. An attempt is made to integrate both concepts and examine Health Insurance Portability and Accountability Act (HIPAA) compliance for each of the examples discussed. The legal regulations that may inform care and standards of practice are reviewed, and the difficulties that arise in assessment and monitoring of the current situation are analyzed. For forensic psychiatrists who may be asked to provide expert opinions regarding malpractice situations pertaining to confidentiality standards, it is important to become acquainted with the new digital language from which these questions may arise.
Download full-text PDF |
Source |
---|
BMC Bioinformatics
January 2025
Solu Healthcare Oy, Kalevankatu 31 A 13, 00100, Helsinki, Finland.
Background: Genomic surveillance is extensively used for tracking public health outbreaks and healthcare-associated pathogens. Despite advancements in bioinformatics pipelines, there are still significant challenges in terms of infrastructure, expertise, and security when it comes to continuous surveillance. The existing pipelines often require the user to set up and manage their own infrastructure and are not designed for continuous surveillance that demands integration of new and regularly generated sequencing data with previous analyses.
View Article and Find Full Text PDFUrban Inform
January 2025
IVL Swedish Environmental Research Institute LTD., PO Box 530 21, SE-400 14 Gothenburg, Sweden.
In response to the demand for advanced tools in environmental monitoring and policy formulation, this work leverages modern software and big data technologies to enhance novel road transport emissions research. This is achieved by making data and analysis tools more widely available and customisable so users can tailor outputs to their requirements. Through the novel combination of vehicle emissions remote sensing and cloud computing methodologies, these developments aim to reduce the barriers to understanding real-driving emissions (RDE) across urban environments.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
Most current research in cloud forensics is focused on tackling the challenges encountered by forensic investigators in identifying and recovering artifacts from cloud devices. These challenges arise from the diverse array of cloud service providers as each has its distinct rules, guidelines, and requirements. This research proposes an investigation technique for identifying and locating data remnants in two main stages: artefact collection and evidence identification.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science & Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.
The Internet of Things (IoT) has seen remarkable advancements in recent years, leading to a paradigm shift in the digital landscape. However, these technological strides have introduced new challenges, particularly in cybersecurity. IoT devices, inherently connected to the internet, are susceptible to various forms of attacks.
View Article and Find Full Text PDFPhysiol Meas
January 2025
University of Duisburg-Essen, Bismarckstr. 81 (BB), Duisburg, 47057, GERMANY.
Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.
Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed
to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!