AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data.

PloS one
OBJECTIVE: This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enhancing interpretability. We compare performance and interpretability of models trained only on struct...

Unlocking the Power of EHRs: Harnessing Unstructured Data for Machine Learning-based Outcome Predictions.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The integration of Electronic Health Records (EHRs) with Machine Learning (ML) models has become imperative in examining patient outcomes due to the vast amounts of clinical data they provide. However, critical information regarding social and behavi...

NG-DTA: Drug-target affinity prediction with n-gram molecular graphs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Drug-target affinity (DTA) prediction is crucial to speed up drug development. The advance in deep learning allows accurate DTA prediction. However, most deep learning methods treat protein as a 1D string which is not informative to models compared t...

iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease.

PLoS computational biology
Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing e...

A Robot-Assisted Framework for Rehabilitation Practices: Implementation and Experimental Results.

Sensors (Basel, Switzerland)
One of the most interesting characteristics of collaborative robots is their ability to be used in close cooperation scenarios. In industry, this facilitates the implementation of human-in-loop workflows. However, this feature can also be exploited i...

Automatic Detection of Dyspnea in Real Human-Robot Interaction Scenarios.

Sensors (Basel, Switzerland)
A respiratory distress estimation technique for telephony previously proposed by the authors is adapted and evaluated in real static and dynamic HRI scenarios. The system is evaluated with a telephone dataset re-recorded using the robotic platform de...

RNA contact prediction by data efficient deep learning.

Communications biology
On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing complement to experimental efforts. Any deep learning on RNA structure, however, is hampered by the sparsit...

Using sequences of life-events to predict human lives.

Nature computational science
Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event se...

Z2F: Heterogeneous graph-based Android malware detection.

PloS one
Android malware is becoming more common, and its invasion of smart devices has brought immeasurable losses to people's lives. Most existing Android malware detection methods extract Android features from the original application files without conside...

Automated detection and recognition system for chewable food items using advanced deep learning models.

Scientific reports
Identifying and recognizing the food on the basis of its eating sounds is a challenging task, as it plays an important role in avoiding allergic foods, providing dietary preferences to people who are restricted to a particular diet, showcasing its cu...