AIMC Topic: Programming Languages

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A Novel Method and Python Library for ECG Signal Quality Assessment.

Studies in health technology and informatics Aug 22, 2024
Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG signal is very prone to being distorted through different sources of artifacts that can later interfere with the diagnostic. For this reason, signal qua...
Artifacts Signal Processing, Computer-Assisted Programming Languages Humans Machine Learning Algorithms Electrocardiography
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A Comparison of LLMs for Use in Generating Synthetic Test Data for Automated Testing of a Patient-Focused, Survey-Based System.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
In the context of a patient-focused, survey-based system, we demonstrated the potential of generative AI to create custom synthetic data using 2 different large language models (GPT 3.5 and Flan T5-XL) in AWS and Azure environments. While we improved...
Humans Natural Language Processing Patient-Centered Care Artificial Intelligence Programming Languages Surveys and Questionnaires
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DeepMind AI creates algorithms that sort data faster than those built by people.

Nature Jun 1, 2023
Humans Artificial Intelligence Algorithms Deep Learning Time Factors Software Data Analysis Programming Languages
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Six tips for better coding with ChatGPT.

Nature Jun 1, 2023
Software Natural Language Processing Programming Languages
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Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...
Proportional Hazards Models Kaplan-Meier Estimate Head and Neck Neoplasms Programming Languages Survival Analysis Neural Networks, Computer Datasets as Topic Deep Learning Machine Learning Biomarkers, Tumor Lung Neoplasms Male Prognosis Humans Biomarkers Female
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dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.

Bioinformatics (Oxford, England) Oct 31, 2022
MOTIVATION: In multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates t...
Humans Machine Learning Programming Languages Software Algorithms Privacy
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Exploration of the Decision Model and Notation (DMN) Standard for Representation of Knowledge Bases Encoded in the Arden Syntax.

Studies in health technology and informatics Jun 6, 2022
CONTEXT: Arden Syntax encodes knowledge as Medical Logic Modules (MLMs). Current work involves improvement of its representation of business processes.
Programming Languages Knowledge Bases
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Deep learning-enhanced, open-source eigenmode expansion.

Optics letters Mar 15, 2022
We present an open-source eigenmode expansion (EME) software package entirely implemented in the Python programming language. Eigenmode expansion Python (EMEPy) utilizes artificial neural networks to reproduce electromagnetic eigenmode field profiles...
Programming Languages Software Deep Learning
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OCTID: a one-class learning-based Python package for tumor image detection.

Bioinformatics (Oxford, England) Nov 5, 2021
MOTIVATION: Tumor tile selection is a necessary prerequisite in patch-based cancer whole slide image analysis, which is labor-intensive and requires expertise. Whole slides are annotated as tumor or tumor free, but tiles within a tumor slide are not....
Humans Neural Networks, Computer Programming Languages Machine Learning Image Processing, Computer-Assisted Datasets as Topic Neoplasms
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Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics Jul 20, 2021
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...
Gene Dosage Signal Transduction Deep Learning Mutation ras Proteins Humans RNA-Seq Neoplasm Proteins Programming Languages Neoplasms
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