Development and Validation of a Deep Learning Predictive Model Combining Clinical and Radiomic Features for Short-Term Postoperative Facial Nerve Function in Acoustic Neuroma Patients

This study presents a predictive model that integrates #Clinical & #Radiomic features to predict short-term #Postoperative #FacialNerve function in patients with #AcousticNeuroma, supporting the refinement of treatment strategies. #medsky

To read: link.springer.com/article/10.1...

📢 Repeatability of #radiomic features

In 759 patients with esophageal cancer and nasopharyngeal carcinoma, repeatability of CT- and PET-derived radiomic features varied by cancer type, region, and imaging modality. Four highly repeatable features consistently predicted survival across both cancers

Radiomics neurobiomarkers for distinguishing mathematical-related areas in children with elevated ADHD symptoms Children with ADHD symptoms are at higher risk of experiencing mathematical difficulties. Individuals with ADHD often exhibit lower mathematical accur…

Excited to share our latest study! We found #radiomic differences in math-related brain areas (frontal & posterior cingulate cortex, hippocampus) in children with #ADHD symptoms vs. controls. Could math difficulties be tied to attention to number? 👇

#Neuro

www.sciencedirect.com/science/arti...

Sennheiser announces single-channel version of Profile Wireless 2.4GHz all-in-one wireless mic system #stagemic #radiomic #liveradiomic tinyurl.com/yudv4kut

Convergence of evolving #AI and #ML techniques:

#multiomic, #spatial imaging, #pathology, #radiomic technologies enable a deeper understanding of #tumor #biology & #precision #oncology, such as building virtual #digitaltwins to optimize trial design.

www.nature.com/articles/s41...

Interested in CT #radiomics for ovarian cancer? This study validates the use of a CT-based #radiomic prognostic vector (RPV) in predicting poor overall survival (OS) in women with high-grade serous #OvarianCancer.

(1/2)

Yiman Li et al. developed a novel hybrid model combining #radiomic and clinical #data to predict tertiary lymphoid structures (TLSs) in hepatocellular carcinoma (HCC), helping identify patients who may benefit from postop targeted immunotherapy.

(1/2)

Adding #radiomic features to conventional radiological feature-based differential diagnosis was investigated, finding it improves the differential diagnosis of benign vs. malignant lung nodules. (Zhou Liu et al.)

#EuropeanRadiology

🔗 https://buff.ly/3VSFRi9

I always draw Alastor's microphone in love with Lucifer. Now, mic-san makes their move 🍎🎙💕 #hazbinhotel #radiomic

Impact of Emerging Deep Learning–Based MR Image... : Journal of Computer Assisted Tomography ted undersampled coronal T2-weighted MR images of the abdomen (1.5 T; Philips Healthcare) from 17 pediatric and adult subjects and reconstructed them using a conventional image reconstruction techniqu...

#deeplearning has contributed to marked improvements in image quality & scan speed - however our research shows that DL recons impact #mri #radiomic features #nofreelunch

journals.lww.com/jcat/abstrac...