Additional file 1 of Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study

Additional file 1. Methods. Fig. S1 Flowchart of patient screening, exclusions, and eligibility. Fig. S2 Subgroup analysis of confusion matrices showing pathological outcomes vs. Generative Pretrained Transformer (GPT)-4 biopsy recommendations across 3 cohorts. Fig. S3 Confusion matrices displaying pathological outcomes vs. Generative Pretrained Transformer (GPT)-4 recommendations for biopsy (n = 912). Fig. S4 Interface of the PostAIGuide platform. Table S1 Two examples of Chain of Thought (CoT) responses. Table S2 Two typical examples of “dialogues” with Generative Pretrained Transformer (GPT)-4 and the generated reports. Table S3 Quantitative results from the confusion matrix. Table S4 Three relatively challenging questions and GPT-4’s responses.

Institutions

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29486317
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Additional file 1 of Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study

Figshare
Prostate Cancer Diagnosis and Treatment
article

Additional file 1 of Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study

article en

Abstract

Additional file 1. Methods. Fig. S1 Flowchart of patient screening, exclusions, and eligibility. Fig. S2 Subgroup analysis of confusion matrices showing pathological outcomes vs. Generative Pretrained Transformer (GPT)-4 biopsy recommendations across 3 cohorts. Fig. S3 Confusion matrices displaying pathological outcomes vs. Generative Pretrained Transformer (GPT)-4 recommendations for biopsy (n = 912). Fig. S4 Interface of the PostAIGuide platform. Table S1 Two examples of Chain of Thought (CoT) responses. Table S2 Two typical examples of “dialogues” with Generative Pretrained Transformer (GPT)-4 and the generated reports. Table S3 Quantitative results from the confusion matrix. Table S4 Three relatively challenging questions and GPT-4’s responses.

Figshare
Capital University (US), Capital Medical University (CN), Peking University (CN), Beijing Chao-Yang Hospital, Capital Medical University (CN), Shunyi Hospital of Beijing Traditional Chinese Medicine Hospital (CN), Peking University Third Hospital (CN), Beijing Friendship Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 36%
Prostate Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Additional file 1 of Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study · Figshare (2025) | TGRS Research Map | TGRS