Evidence map›Paper›PMID 40969818›Full record

ReviewJuntendo medical journal2025

Basic Uses of Python for Research in Our Laboratory: Examples of Data Analysis, and Processing of Histological Samples Based on the Special Graduate Lecture for Postgraduate Students Presented on January 2025.

Juan Alejandro Oliva Trejo

Abstract readReview
In one paragraph

Review in Juntendo medical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Juan Alejandro Oliva Trejo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Python is one of the most popular programming languages to learn and use. It is ubiquitous in fields like data analysis, artificial intelligence, image processing, robotics, and web development. Its versatility and reliability make it ideal for major companies, including Tesla and Netflix. NASA even uses it to calibrate the James Webb Space Telescope. With the advent of artificial intelligence (AI), writing a Python program can be as simple as prompting an AI assistant for a solution. For research scientists, this lowered barrier could spark a generational change, transforming every research stage from idea conception to publishing. My interest in AI-assisted programming inspired my lecture on how Python can assist PhD students in their work. This lecture begins with basic terminology and presents three mini projects as first steps for learning Python. These projects cover text extraction and analysis, statistical data analysis, and virtually staining histological samples into digital image stacks. Small variations of these projects could lead to code that extracts reagents from manuscripts, creates stunning statistical graphs, and advances histopathological methods.

Indexed as

AIdata analysisimage processingmorphologyPython programming

Identifiers

PMID40969818
PMCPMC12441172

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.