Reply to Letter to the Editor: "Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline".

Fuhai Sun, Junyan Lyu, Si Jian, Yuanyuan Qin, Xiaoying Tang

Abstract readLetterComment

In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Reducing radiation dose in routine CT scans: an AI-driven approach with deep learning-based dual-energy CT reconstruction.European radiology · 2024
Article

4 · The record

Corrections and comments

Comment on
Magnetic Resonance Parkinsonism Index: diagnostic accuracy of a fully automated algorithm in comparison with the manual measurement in a large Italian multicentre study in patients with progressive supranuclear palsy.2017

5 · Who and what money

Authors and funding

5 authors.

Fuhai SunDepartment of Electronic and Electrical Engineering, College of Engineering, Southern University of Science and Technology, Xili, Nanshan, Shenzhen, Guangdong, 518055, People's Republic of China.

Junyan LyuDepartment of Electronic and Electrical Engineering, College of Engineering, Southern University of Science and Technology, Xili, Nanshan, Shenzhen, Guangdong, 518055, People's Republic of China.

Si JianDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue, Wuhan, People's Republic of China.

Yuanyuan QinDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue, Wuhan, People's Republic of China. qinyuanyuan-1021@163.com.

Xiaoying TangDepartment of Electronic and Electrical Engineering, College of Engineering, Southern University of Science and Technology, Xili, Nanshan, Shenzhen, Guangdong, 518055, People's Republic of China. tangxy@sustech.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningParkinsonian DisordersHumansMagnetic Resonance ImagingMagnetic Resonance Spectroscopy

Identifiers

PMID37831138

DOI10.1007/s00330-023-10290-2

What OpenQuestion holds

Textmetadata

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.