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Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Science and engineering ethics
Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI t...

Effect of incremental feature enrichment on healthcare text classification system: A machine learning paradigm.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Healthcare tweets are particularly challenging due to its sparse layout and its limited character size. Compared to previous method based on "bag of words" (BOW) model, this study uniquely identifies the enrichment protocol ...

Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study.

PloS one
A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, t...

Information flow reveals prediction limits in online social activity.

Nature human behaviour
Modern society depends on the flow of information over online social networks, and users of popular platforms generate substantial behavioural data about themselves and their social ties. However, it remains unclear what fundamental limits exist when...

Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification.

Journal of medical Internet research
BACKGROUND: Instagram, with millions of posts per day, can be used to inform public health surveillance targets and policies. However, current research relying on image-based data often relies on hand coding of images, which is time-consuming and cos...

An unsupervised and customizable misspelling generator for mining noisy health-related text sources.

Journal of biomedical informatics
BACKGROUND: Data collection and extraction from noisy text sources such as social media typically rely on keyword-based searching/listening. However, health-related terms are often misspelled in such noisy text sources due to their complex morphology...

Identifying substance use risk based on deep neural networks and Instagram social media data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Social media may provide new insight into our understanding of substance use and addiction. In this study, we developed a deep-learning method to automatically classify individuals' risk for alcohol, tobacco, and drug use based on the content from th...

Machine learning to support social media empowered patients in cancer care and cancer treatment decisions.

PloS one
BACKGROUND: A primary variant of social media, online support groups (OSG) extend beyond the standard definition to incorporate a dimension of advice, support and guidance for patients. OSG are complementary, yet significant adjunct to patient journe...

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

AMA journal of ethics
A significant proportion of elderly and psychiatric patients do not have the capacity to make health care decisions. We suggest that machine learning technologies could be harnessed to integrate data mined from electronic health records (EHRs) and so...

Advancing the State of the Art in Clinical Natural Language Processing through Shared Tasks.

Yearbook of medical informatics
OBJECTIVES:  To review the latest scientific challenges organized in clinical Natural Language Processing (NLP) by highlighting the tasks, the most effective methodologies used, the data, and the sharing strategies.