Predicting Non-Mass Breast Cancer Utilizing Ultrasound and Molybdenum Target X-Ray Characteristics

Using both ultrasound and molybdenum target X-ray diagnostics can increase the accuracy of non-mass breast cancer detection. The findings of this study have the potential to augment the detection rate of non-lumpy breast cancer and provide an imaging basis for enhancing the prognosis of individuals with breast cancer.

Authors

Institutions

Publication Details

Journal
Journal of Multidisciplinary Healthcare
Published
2024-09-01
DOI
https://doi.org/10.2147/jmdh.s473370
Citations
2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting Non-Mass Breast Cancer Utilizing Ultrasound and Molybdenum Target X-Ray Characteristics

Ruiqi Fan, Na Mi, Tingting Li, Jingjie Wang et al.
2 citations
Journal of Multidisciplinary Healthcare
Radiomics and Machine Learning in Medical Imaging
0.81
article

Predicting Non-Mass Breast Cancer Utilizing Ultrasound and Molybdenum Target X-Ray Characteristics

Ruiqi Fan, Na Mi, Tingting Li, Jingjie Wang, Zhuoran Wang, Chunmei Jia, J. Quan, Xufeng Cao
article en
2 citations

Abstract

Using both ultrasound and molybdenum target X-ray diagnostics can increase the accuracy of non-mass breast cancer detection. The findings of this study have the potential to augment the detection rate of non-lumpy breast cancer and provide an imaging basis for enhancing the prognosis of individuals with breast cancer.

Journal of Multidisciplinary HealthcareVol. Volume 17
Shanxi Medical University (CN), First Hospital of Shanxi Medical University (CN), Chinese People's Liberation Army (CN)
Shanxi Provincial Key Research and Development Project
Good health and well-being
Openalex Percentile: Top 26%
Radiomics and Machine Learning in Medical Imaging
0.81
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.