Medicine
When silence is safer: a review and decision-theoretic framework for LLM abstention in healthcare
Large language models (LLMs) are designed to generate answers to user prompts, which often drives them to respond even when uncertainty is high, information is incomplete, or a refusal would be more appropriate. In healthcare, this tendency can be dangerous: confidently stated but inaccurate medical…
Advancing regulatory variant effect prediction with AlphaGenome
Deep learning models that predict functional genomic measurements from DNA sequences are powerful tools for deciphering the genetic regulatory code. Existing methods involve a trade-off between input sequence length and prediction resolution, thereby limiting their modality scope and performance1,2,3,4,5. We present AlphaGenome, a unified DNA…
Federated Learning: Issues in Medical Application
In this presentation, the current issues to make federated learning flawlessly useful in the real world will be briefly overviewed. They are related to data/system heterogeneity, client management, traceability, and security. Also, we introduce the modularized federated learning framework, we currently develop, to experiment various…
Highly accurate protein structure prediction with AlphaFold
Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.
Unsupervised deep clustering and reinforcement learning can accurately segment MRI brain tumors with very small training sets
«We have demonstrated a proof-of-principle application of unsupervised deep clustering and reinforcement learning to segment brain tumors. The approach represents human-allied AI that requires minimal input from the radiologist without the need for hand-traced annotation».
Side-Channel Sensing: Exploiting Side-Channels to Extract Information for Medical Diagnostics and Monitoring
Information within systems can be extracted through side-channels; unintended communication channels that leak information. The concept of side-channel sensing is explored, in which sensor data is analysed in non-trivial ways to recover subtle, hidden or unexpected information.
Medical notes summariser: «Characterizing the Value of Information in Medical Notes»
Machine learning models depend on the quality of input data. As electronic health records are widely adopted, the amount of data in health care is growing, along with complaints about the quality of medical notes.
Probabilistic Machine Learning for Healthcare
Machine learning can be used to make sense of healthcare data. Probabilistic machine learning models help provide a complete picture of observed data in healthcare. In this review, we examine how probabilistic machine learning can advance healthcare. We consider challenges in the predictive model building…
Artificial Intelligence in Medical Imaging
«This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging».
Transforming Health Care Through AI Revolutions
I will discuss relevant AI thrusts at NIST on health care informatics, focusing on the use of machine learning, knowledge representation and natural language processing. I will also discuss the need for explanations in AI systems (XAI) and current state of the art in medical…
Undergraduate Diagnostic Imaging Fundamentals
The structure and content of this work has been guided by the curricula developed by the European Society of Radiology, the Royal College of Radiologists, the Alliance of Medical Student Educators in Radiology, with guidance and input from Canadian Radiology Undergraduate Education Coordinators, and the…
Machine learning in medicine: a practical introduction
Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providing a conceptual introduction to machine learning alongside a practical guide to…
Digital Health And The Fight Against The COVID-19 Pandemic
You will find up-to-date, reliable information about the latest innovations, technologies, and trends in the context of COVID-19, and the best examples of 14 digital health technologies already sent to the battle successfully
Machine Learning for Medical Imaging Analysis Demystified
This lecture will outline the fundamental ML processes involved in medical image analysis. Achieving prediction and classification for CAD applications will also be discussed. Some preliminary ideas of 3D reconstruction and viewing as applied in medical image analysis will also be presented.
Artificial Intelligence and Machine Learning in Software as a Medical Device: discussion Paper and Request for Feedback
Artificial intelligence and machine learning technologies have the potential to transform health care by deriving new and important insights from the vast amount of data generated during the delivery of health care every day. Medical device manufacturers are using these technologies to innovate their products…
ICT security certification opportunities in the healthcare sector
Digital solutions for healthcare open a plethora of new possibilities in this area. They provide a technical base for easy testing, they improve significantly the quality of service by allowing immediate access to medical data – results of tests, history of treatment; they facilitate correct…
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications
Recent technological advances such as wearable sensing devices, real-time data streaming, machine learning, and deep learning approaches have increased interest in electroencephalographic (EEG) based BCI for translational and healthcare applications.
Células y proteínas: el modelo SNARE-CNN (red neuronal convolucional 2D)
Usando el modelo, en sus conclusiones, los autores señalan que las nuevas proteínas SNARE pueden identificarse con precisión y usarse para el desarrollo de fármacos. Y tratándose de enfermedades como las neurodegenerativas, mentales y el cáncer podemos y debemos interesarnos por este trabajo aplicado…
Cybersecurity
Sequence Feature Extraction for Malware Family Analysis via Graph Neural Network
Malicious software (malware) causes much harm to our devices and life. We are eager to understand the malware behavior and the threat it made. Most of the record files of malware are variable length and text-based files with time stamps, such as event log data…
Framework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices
The continuous appearance and improvement of mobile devices in the form of smartwatches, smartphones and other similar devices has led to a growing and unfair interest in putting their users under the magnifying glass and control of applications.
‘Framework’ basado en imágenes parametrizadas sobre ResNet para identificar intrusiones en ‘smartwatches’ u otros dispositivos afines
La continua aparición y mejora de dispositivos móviles en forma de ‘smartwatches’, ‘smartphones’ y otros dispositivos similares ha propicio un creciente y desleal interés en poner bajo la lupa y el control de los aplicativos a sus usuarios. De forma ofuscada por los fabricantes.
Side-Channel Sensing: Exploiting Side-Channels to Extract Information for Medical Diagnostics and Monitoring
Information within systems can be extracted through side-channels; unintended communication channels that leak information. The concept of side-channel sensing is explored, in which sensor data is analysed in non-trivial ways to recover subtle, hidden or unexpected information.
WHAT IS [MEANINGFUL PRIVACY]*
Meaningful privacy and how it is applied in technology will be the focus of 60 privacy preserving leaders from around the globe during the OpenMined Privacy conference Sept 26 and 27 2020 with more than 2000 in attendance virtually.
Disposable Identities are Elemental(s) in IoT
Rob wants to argue that if intent is linked to an incorrect assessment of identity, and thus not central to an ethics of behaviour, then this opens up an actionable set of actors actually at play in the digtial (IoT, 5G, AI) namely: objects (with…
OpenMined: open source to make privacy-preserving of AI technologies
With OpenMined, an AI model can be governed by multiple owners and trained securely on an unseen, distributed dataset.The mission of the OpenMined community is to create an accessible ecosystem of tools for private, secure, multi-owner governed AI
Privacy Preserving AI – Andrew Trask, OpenMined
Learn the basics of secure and private AI techniques, including federated learning and secure multi-party computation. In this talk, Andrew Trask of OpenMined highlights the importance of privacy preserving machine learning, and how to use privacy-focused tools like PySyft.
Trainings for Cybersecurity Specialists
«ENISA CSIRT training material was introduced in 2008. In 2012, 2013 and 2014 it was complemented with new exercise scenarios containing essential material for success in the CSIRT community and in the field of information security. In these pages you will find the ENISA CSIRT…
EUROPEAN CYBER SECURITY CHALLENGE 2020 (Change dates)
(Change of dates to 2021).Top cyber talents from each participating country will meet in Vienna to network and collaborate and finally compete against each other. Contestants will be challenged in solving security related tasks from domains such as web security, mobile security, crypto puzzles, reverse…
TechDispatch #1/2020: Contact Tracing with Mobile Applications
In public health, contact tracing is the process to identify individuals who have been in contact with infected persons. Proximity tracing with smartphone applications and sensors could support contact tracing. It involves processing of sensitive personal data.
Cumplimiento normativo y seguridad TI en IoT
La conectividad y el tratamiento masivo de datos son dos pilares esenciales para el desarrollo de estos sistemas, los cuales, a su vez, introducen riesgos de seguridad y privacidad que deben ser tratados adecuadamente.
INTERPOL: Impact of COVID-19 on Financial Crimes, webinar
The complexity of acting against cybercriminal internet domains was discussed; also on the techniques used in cybercrime… Information and detailed well-explained was offered by INTERPOL members, on how to detect and act in most cases.
Tools on Cybercrime & Electronic Evidence Empowering you
Welcome to the Search portal of the Cybercrime
CSIRTs and criminal justice authorities
CSIRTs and criminal justice authorities – good practices of collaboration on cybercrime and electronic evidence (webinar, Council Europe)
III CONGRESO AUDITORÍA Y GRC (ISACA Madrid Chapter)
Este congreso, motivado por la creciente sensibilidad de las compañías en materia de Gobierno, Riesgo y Cumplimiento, se enfoca en generar una visión global de los procesos, gestión de riesgos, fraude, control interno y cumplimiento normativo y legislativo, sin dejar de lado la metodología y…
Encrypted Traffic Analysis
This report explores the current state of affairs in Encrypted Traffic Analysis and in particular discusses research and methods in 6 key use cases; viz. application identification, network analytics, user information identification, detection of encrypted malware, file/device/website/location fingerprinting and DNS tunnelling detection.
When Autonomous Vehicles Are Hacked, Who Is Liable?
Who might face civil liability if autonomous vehicles (AVs) are hacked to steal data or inflict mayhem, injuries, and damage? How will the civil justice and insurance systems adjust to handle such claims? RAND researchers addressed these questions to help those in the automotive, technology,…
Free Cybersecurity Training
Provides instruction in the basic of network security in depth. Includes security objectives, security architecture, security models and security layers; risk management, network security policy, and security training. Includes the give security keys, confidentiality integrity, availability, accountability and auditability. Lecture 3 hours per week.
Standardisation in support of the Cybersecurity Certification
The document presents the value of the cybersecurity standardisation efforts for certification, the roles and responsibilities of Standards Developing Organisations (SDOs) in this context, and discusses various ways how standardisation can support efficiently the process of certification schemes creation by following a step by step…
Cyber Europe 2020: Preparing healthcare sector to respond to cyber crises
In 2020, European countries and the EU Agency for Cybersecurity (ENISA) should have organised the 6th pan European cyber crisis exercise, Cyber Europe 2020 (CE2020). However, due to the current health crisis Cyber Europe will be shifted to a later date, yet to be announce….
Working from home during the #COVID19 crisis
The EU Agency for #Cybersecurity (ENISA) shares its cybersecurity recommendations on working remotely during the COVID-19 crisis.
Cyber Attack Detection thanks to Machine Learning Algorithms
Cybersecurity attacks are growing both in frequency and sophistication over the years. This increasing sophistication and complexity call for more advancement and continuous innovation in defensive strategies. Traditional methods of intrusion detection and deep packet inspection, while still largely used
and recommended, are no longer sufficient…
Guía de diseño de COBIT 2019
Guía de diseño de COBIT 2019: el diseño de una solución de gobernanza de la información y la tecnología es una publicación innovadora para el marco de trabajo de COBIT.
Estándares y seguridad en el uso humano de la IA
https://youtu.be/N6ZLzzAZ_nQ Fig. I A. 9.1.1- Atrévete a soñar en GRANDE: los estándares empoderan a los innovadores. Crédito imag. (ISO). URL: https://youtu.be/N6ZLzzAZ_nQ Autor: Juan Antonio Lloret Egea | https://orcid.org/0000-0002-6634-3351|© 2019. Licencia de uso y distribución: Creative Commons CC BY 4.0.|Escrito: 20/10/2019. Actualizado:20/10/2019. DOI 10.13140/RG.2.2.26418.15045 | 9.1-1.- Introducción El…
Automotive
Model-based Decision Making with Imagination for Autonomous Parking
Autonomous parking technology is a key concept within autonomous driving research. This paper will propose…
YOLOX: Exceeding YOLO Series in 2021
We switch the YOLO detector to an anchor-free manner and conduct other advanced detection techniques,…
YOLOP: You Only Look Once for Panoptic Driving Perception
A panoptic driving perception system is an essential part of autonomous driving. A high-precision and…
Research and innovation in smart mobility and services in Europe
For smart mobility to be cost-efficient and ready for future needs, adequate research and innovation…
Explaining Autonomous Driving by Learning End-to-End Visual Attention
In this work we propose to train an imitation learning based agent equipped with an…
IEEE: Certification Program for Autonomous and Intelligent Systems (ECPAIS) is ready for phase II
#IEEE Invites Companies, Governments and Other Stakeholders Globally to Expand on #Ethics #Certification Program for…
When Autonomous Vehicles Are Hacked, Who Is Liable?
Who might face civil liability if autonomous vehicles (AVs) are hacked to steal data or…
El Programa de Certificación de Ética para Sistemas Autónomos e Inteligentes (ECPAIS)
El objetivo del Programa de Certificación de Ética para Sistemas Autónomos e Inteligentes (ECPAIS) del…