Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques
Objective The proper handling of missing values is critical to delivering reliable estimates
and decisions, especially in high-stakes fields such as clinical research. In response to the …
and decisions, especially in high-stakes fields such as clinical research. In response to the …
Artificial intelligence for social good: A survey
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …
advance artificial intelligence to address societal issues and improve the well-being of the …
Missing value imputation methods for electronic health records
Electronic health records (EHR) are patient-level information, eg, laboratory tests and
questionnaires, stored in electronic format. Compared to physical records, the EHR …
questionnaires, stored in electronic format. Compared to physical records, the EHR …
[HTML][HTML] Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review
Background Wearable technologies have become increasingly prominent in health care.
However, intricate machine learning and deep learning algorithms often lead to the …
However, intricate machine learning and deep learning algorithms often lead to the …
Social dimensions impact individual sleep quantity and quality
While sleep positively impacts well-being, health, and productivity, the effects of societal
factors on sleep remain underexplored. Here we analyze the sleep of 30,082 individuals …
factors on sleep remain underexplored. Here we analyze the sleep of 30,082 individuals …
Healthwalks: Sensing fine-grained individual health condition via mobility data
Can health conditions be inferred from an individual's mobility pattern? Existing research
has discussed the relationship between individual physical activity/mobility and well-being …
has discussed the relationship between individual physical activity/mobility and well-being …
An ensemble classification model for depression based on wearable device sleep data
Depression is one of the most common mental disorders, with sleep disturbances as typical
symptoms. With the popularity of wearable devices increasing in recent years, more and …
symptoms. With the popularity of wearable devices increasing in recent years, more and …
Affective state during physiotherapy and its analysis using machine learning methods
Invasive or uncomfortable procedures especially during healthcare trigger emotions.
Technological development of the equipment and systems for monitoring and recording …
Technological development of the equipment and systems for monitoring and recording …
Leveraging Prototype Patient Representations with Feature-Missing-Aware Calibration to Mitigate EHR Data Sparsity
Electronic Health Record (EHR) data frequently exhibits sparse characteristics, posing
challenges for predictive modeling. Current direct imputation such as matrix imputation …
challenges for predictive modeling. Current direct imputation such as matrix imputation …
An Experimental Evaluation of Imputation Models for Spatial-Temporal Traffic Data
Traffic data imputation is a critical preprocessing step in intelligent transportation systems,
enabling advanced transportation services. Despite significant advancements in this field …
enabling advanced transportation services. Despite significant advancements in this field …