Enhancing deep learning for demand forecasting to address large data gaps DOI Creative Commons
Chirine Riachy, Mengda He, Sina Joneidy

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 126200 - 126200

Published: Dec. 1, 2024

Language: Английский

Radiogenomics: bridging the gap between imaging and genomics for precision oncology DOI Creative Commons
Wenle He, Wenhui Huang, Lu Zhang

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(9)

Published: Sept. 1, 2024

Abstract Genomics allows the tracing of origin and evolution cancer at molecular scale underpin modern diagnosis treatment systems. Yet, biomarker‐guided clinical decision‐making encounters major challenges in realm individualized medicine, consisting invasiveness procedures sampling errors due to high tumor heterogeneity. By contrast, medical imaging enables noninvasive global characterization tumors a low cost. In recent years, radiomics has overcomes limitations human visual evaluation by high‐throughput quantitative analysis, enabling comprehensive utilization vast amount information underlying radiological images. The cross‐scale integration genomics (hereafter radiogenomics) enormous potential enhance decoding act as catalyst for digital precision medicine. Herein, we provide overview current framework applications radiogenomics patient care. We also highlight research advances illustrate how can address common problems solid such breast cancer, lung glioma. Finally, analyze existing literature outline propose solutions, while identifying future pathways. believe that perspectives shared this survey will valuable guide researchers aiming advance oncology.

Language: Английский

Citations

1

Enhancing deep learning for demand forecasting to address large data gaps DOI Creative Commons
Chirine Riachy, Mengda He, Sina Joneidy

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 126200 - 126200

Published: Dec. 1, 2024

Language: Английский

Citations

1