AIMC Topic: Privacy

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Shaping technologies for older adults with and without dementia: Reflections on ethics and preferences.

Health informatics journal
As a result of several years of European funding, progressive introduction of assistive technologies in our society has provided many researchers and companies with opportunities to develop new information and communication technologies aimed at over...

Distributed learning on 20 000+ lung cancer patients - The Personal Health Train.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) pro...

Privacy-enhanced multi-party deep learning.

Neural networks : the official journal of the International Neural Network Society
In multi-party deep learning, multiple participants jointly train a deep learning model through a central server to achieve common objectives without sharing their private data. Recently, a significant amount of progress has been made toward the priv...

KETOS: Clinical decision support and machine learning as a service - A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services.

PloS one
BACKGROUND AND OBJECTIVE: To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in...

Protecting the Privacy of Cancer Patients Using Fuzzy Association Rule Hiding.

Asian Pacific journal of cancer prevention : APJCP
Objective: Privacy protection in the medical field means the protection of individuals from being associated with undesirable conditions, diagnoses or treatments (Sensitive Attributes). The problem of knowledge discovery from health care data by appl...

A machine learning based approach to identify protected health information in Chinese clinical text.

International journal of medical informatics
BACKGROUND: With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of id...

Protecting Your Patients' Interests in the Era of Big Data, Artificial Intelligence, and Predictive Analytics.

Journal of the American College of Radiology : JACR
The Hippocratic oath and the Belmont report articulate foundational principles for how physicians interact with patients and research subjects. The increasing use of big data and artificial intelligence techniques demands a re-examination of these pr...

Supporting Regularized Logistic Regression Privately and Efficiently.

PloS one
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects...