Natural language processing in law: Prediction of outcomes in the higher courts of Turkey
Natural language processing (NLP) based approaches have recently received attention for
legal systems of several countries. It is of interest to study the wide variety of legal systems …
legal systems of several countries. It is of interest to study the wide variety of legal systems …
Multilingual topic modeling for tracking COVID-19 trends based on Facebook data analysis
Social data has shown important role in tracking, monitoring and risk management of
disasters. Indeed, several works focused on the benefits of social data analysis for the …
disasters. Indeed, several works focused on the benefits of social data analysis for the …
A novel text classification technique using improved particle swarm optimization: A case study of Arabic language
We propose a novel text classification model, which aims to improve the performance of
Arabic text classification using machine learning techniques. One of the effective solutions in …
Arabic text classification using machine learning techniques. One of the effective solutions in …
Improving clinical trial design using interpretable machine learning based prediction of early trial termination
E Kavalci, A Hartshorn - Scientific reports, 2023 - nature.com
This study proposes using a machine learning pipeline to optimise clinical trial design. The
goal is to predict early termination probability of clinical trials using machine learning …
goal is to predict early termination probability of clinical trials using machine learning …
Latent Dirichlet Allocation in predicting clinical trial terminations
S Geletta, L Follett, M Laugerman - BMC medical informatics and decision …, 2019 - Springer
Background This study used natural language processing (NLP) and machine learning (ML)
techniques to identify reliable patterns from within research narrative documents to …
techniques to identify reliable patterns from within research narrative documents to …
Predictive modeling of clinical trial terminations using feature engineering and embedding learning
ME Elkin, X Zhu - Scientific reports, 2021 - nature.com
In this study, we propose to use machine learning to understand terminated clinical trials.
Our goal is to answer two fundamental questions:(1) what are common factors/markers …
Our goal is to answer two fundamental questions:(1) what are common factors/markers …
[PDF][PDF] Deep learning-based risk prediction for interventional clinical trials based on protocol design: A retrospective study
Success rate of clinical trials (CTs) is low, with the protocol design itself being considered a
major risk factor. We aimed to investigate the use of deep learning methods to predict the …
major risk factor. We aimed to investigate the use of deep learning methods to predict the …
Understanding and predicting COVID-19 clinical trial completion vs. cessation
ME Elkin, X Zhu - Plos one, 2021 - journals.plos.org
As of March 30 2021, over 5,193 COVID-19 clinical trials have been registered through
Clinicaltrial. gov. Among them, 191 trials were terminated, suspended, or withdrawn …
Clinicaltrial. gov. Among them, 191 trials were terminated, suspended, or withdrawn …
On graph construction for classification of clinical trials protocols using graph neural networks
A recent trend in health-related machine learning proposes the use of Graph Neural
Networks (GNN's) to model biomedical data. This is justified due to the complexity of …
Networks (GNN's) to model biomedical data. This is justified due to the complexity of …
Predicting intervention approval in clinical trials through multi-document summarization
G Katsimpras, G Paliouras - arXiv preprint arXiv:2204.00290, 2022 - arxiv.org
Clinical trials offer a fundamental opportunity to discover new treatments and advance the
medical knowledge. However, the uncertainty of the outcome of a trial can lead to …
medical knowledge. However, the uncertainty of the outcome of a trial can lead to …