L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts
Computer Graphics Forum, EarlyView.L‐VISP is a human‐machine solution that uses visual analytics for LSTM modelling in clinical research. L‐VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context.
C. Floricel +6 more
wiley +1 more source
A novel bidirectional LSTM deep learning approach for COVID-19 forecasting. [PDF]
Sci Rep, 2023 Aung NN, Pang J, Chua MCH, Tan HX.
europepmc +1 more source
, 2019 A bidirectional LSTM combined with an additional LSTM layer, followed by a dense decision layer with one output neuron activated by a sigmoid function. Overall, we have 16 hidden units in our LSTM layer.
Yuqian Zhou (6928082) +4 more
core +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source
Retracted: IoT-Based Wearable Sensors and Bidirectional LSTM Network for Action Recognition of Aerobics Athletes. [PDF]
J Healthc Eng, 2023 Healthcare Engineering JO.
europepmc +1 more source
Quantitative Biology, Volume 14, Issue 4, December 2026.Abstract Single‐cell RNA sequencing (scRNA‐seq) generates high‐dimensional transcriptomic data but is severely affected by dropout events, which obscure true gene–gene relationships. These missing values introduce bias into downstream analyses, complicate data processing, and reduce analytical efficiency.
Shuang Xu +3 more
wiley +1 more source
Enhancing efficiency and capacity of telehealth services with intelligent triage: a bidirectional LSTM neural network model employing character embedding. [PDF]
BMC Med Inform Decis Mak, 2023 Shi J +6 more
europepmc +1 more source
Predicting ICU mortality by supervised bidirectional LSTM networks
, 2018 Mortality prediction in the Intensive Care Unit (ICU) is considered as one of critical steps for the treatment of patients in serious condition. It is a big challenge to model time-series variables for mortality prediction in ICU, because physiological ...
X Fan (7674161) +5 more
core
Large Language Models and Agentic AI for Vulnerability Management: A Systematic Review
Expert Systems, Volume 43, Issue 11, November 2026.ABSTRACT Large Language Models (LLMs), pretrained language and code models and agentic artificial intelligence are increasingly being investigated across the vulnerability‐management lifecycle. However, the evidence remains fragmented across code‐level prediction, vulnerability‐intelligence enrichment, exploit‐oriented evaluation, automated repair and ...
Yasamin Akrami +2 more
wiley +1 more source
DLC-ac4C: A Prediction Model for N4-acetylcytidine Sites in Human mRNA Based on DenseNet and Bidirectional LSTM Methods. [PDF]
Curr Genomics, 2023 Jia J, Cao X, Wei Z.
europepmc +1 more source