Ethical Surveillance: Applying Deep Learning and Contextual Awareness for the Benefit of Persons Living with Dementia

A significant proportion of the population has become used to sharing private information on the internet with their friends. This information can leak throughout their social network and the extent that personal information propagates can depend on the privacy policy of large corporations. In an era of artificial intelligence, data mining, and cloud computing, is it necessary to share personal information with unidentified people? Our research shows that deep learning is possible using relatively low capacity computing. When applied, this demonstrates promising results in spatio-temporal positioning of subjects, in prediction of movement, and assessment of contextual risk. A private surveillance system is particularly suitable in the care of those who may be considered vulnerable

Results of Stereotactic Radiation Therapy (SABR) in Early Stage Lung Cancer: Turkish Radiation Oncology Group (TROG) Study

WOS: 000454014503151

A Survey on Ambient Sensor-Based Abnormal Behaviour Detection for Elderly People in Healthcare

Peer reviewed: TrueWith advances in machine learning and ambient sensors as well as the emergence of ambient assisted living (AAL), modeling humans’ abnormal behaviour patterns has become an important assistive technology for the rising elderly population in recent decades. Abnormal behaviour observed from daily activities can be an indicator of the consequences of a disease that the resident might suffer from or of the occurrence of a hazardous incident. Therefore, tracking daily life activities and detecting abnormal behaviour are significant in managing health conditions in a smart environment. This paper provides a comprehensive and in-depth review, focusing on the techniques that profile activities of daily living (ADL) and detect abnormal behaviour for healthcare. In particular, we discuss the definitions and examples of abnormal behaviour/activity in the healthcare of elderly people. We also describe the public ground-truth datasets along with approaches applied to produce synthetic data when no real-world data are available. We identify and describe the key facets of abnormal behaviour detection in a smart environment, with a particular focus on the ambient sensor types, datasets, data representations, conventional and deep learning-based abnormal behaviour detection methods. Finally, the survey discusses the challenges and open questions, which would be beneficial for researchers in the field to address.</jats:p

Medically Inoperable Early-Stage Lung Cancer Treated with Stereotactic Ablative Radiation Therapy (SABR): Multicenter Study of Turkish Radiation Oncology Group (TROG)

60th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) -- OCT 21-24, 2018 -- San Antonio, TXWOS: 000447811602068…Amer Soc Radiat Onco