R.I.P.
π»
Ghosted
Smartphones in Mental Health: Detecting Depressive and Manic Episodes
October 06, 2015 Β· Declared Dead Β· π IEEE pervasive computing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Venet Osmani, Agnes Gruenerbl, Gernot Bahle, Christian Haring, Paul Lukowicz, Oscar Mayora
arXiv ID
1510.01665
Category
cs.HC: Human-Computer Interaction
Citations
79
Venue
IEEE pervasive computing
Last Checked
5 months ago
Abstract
An observational study with patients diagnosed with bipolar disorder investigates whether data from smartphone sensors can be used to recognize bipolar disorder episodes and detect behavior changes that can signal an onset of an episode using objective data.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted