AIMC Topic: Programming Languages

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optiGAN: a deep learning-based alternative to optical photon tracking in Python-based GATE (10+).

Physics in medicine and biology
To accelerate optical photon transport simulations in the GATE medical physics framework using a generative adversarial network (GAN), while ensuring high modeling accuracy. Traditionally, detailed optical Monte Carlo methods have been the gold stand...

Machine learning: Python tools for studying biomolecules and drug design.

Molecular diversity
The increasing adoption of computational methods and artificial intelligence in scientific research has led to a growing interest in versatile tools like Python. In the fields of medical chemistry, biochemistry, and bioinformatics, Python has emerged...

Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of med...

Comparison of ChatGPT-4o, Google Gemini 1.5 Pro, Microsoft Copilot Pro, and Ophthalmologists in the management of uveitis and ocular inflammation: A comparative study of large language models.

Journal francais d'ophtalmologie
PURPOSE: The aim of this study was to compare the latest large language models (LLMs) ChatGPT-4o, Google Gemini 1.5 Pro and Microsoft Copilot Pro developed by three different companies, with each other and with a group of ophthalmologists, to reveal ...

Unveiling the power of R: a comprehensive perspective for laboratory medicine data analysis.

Clinical chemistry and laboratory medicine
R language has gained traction in laboratory medicine for its statistical power and dynamic tools like RMarkdown and RShiny. However, there is limited literature summarizing R packages and functions tailored for laboratory medicine, making it difficu...

Predicting software reuse using machine learning techniques-A case study on open-source Java software systems.

PloS one
Software reuse is an essential practice to increase efficiency and reduce costs in software production. Software reuse practices range from reusing artifacts, libraries, components, packages, and APIs. Identifying suitable software for reuse requires...

CPRS: a clinical protocol recommendation system based on LLMs.

International journal of medical informatics
BACKGROUND: As fundamental documents in clinical trials, clinical trial protocols are intended to ensure that trials are conducted according to the objectives set by researchers. The advent of large models with superior semantic performance compared ...

How Good (Or Bad) Are LLMs at Detecting Misleading Visualizations?

IEEE transactions on visualization and computer graphics
In this study, we address the growing issue of misleading charts, a prevalent problem that undermines the integrity of information dissemination. Misleading charts can distort the viewer's perception of data, leading to misinterpretations and decisio...

Large Language Models can Help with Biostatistics and Coding Needed in Radiology Research.

Academic radiology
INTRODUCTION: Original research in radiology often involves handling large datasets, data manipulation, statistical tests, and coding. Recent studies show that large language models (LLMs) can solve bioinformatics tasks, suggesting their potential in...

MolPipeline: A Python Package for Processing Molecules with RDKit in Scikit-learn.

Journal of chemical information and modeling
The open-source package scikit-learn provides various machine learning algorithms and data processing tools, including the Pipeline class, which allows users to prepend custom data transformation steps to the machine learning model. We introduce the ...