Latest AI and machine learning research in oncology/hematology for healthcare professionals.
The principal use of mass cytometry is to identify distinct cell types and changes in their composition, phenotype and function in different samples and conditions. Combining data from different studies has the potential to increase the power of these discoveries in diverse fields such as immunology, oncology and infection. However, current tools are lacking in scalable, reproducible and automated...
Silencers are noncoding DNA sequence fragments located on the genome that suppress gene expression. The variation of silencers in specific cells is closely related to gene expression and cancer development. Computational approaches that exclusively rely on DNA sequence information for silencer identification fail to account for the cell specificity of silencers, resulting in diminished accuracy. D...
<b><br>Introduction:</b> Neoadjuvant chemotherapy (NAC) is a part of the current standard of care in a locally advanced gastric aden...
Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (I...
OBJECTIVE: To evaluate the effectiveness of robot-guided percutaneous fixation and decompression via small incision in treatment of advanced thoracolu...
PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the field of clinical oncology, including early diagn...
MOTIVATION: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate pers...
To evaluate the impact of a reduced iodine load using deep learning reconstruction (DLR) on the hepatic parenchyma compared to conventional iterative ...
PURPOSE: This study investigated the oncological and functional surgical outcomes for patients with renal tumor who underwent robot-assisted partial n...
Thyroid cancer is the most common malignant endocrine tumor. The key test to assess preoperative risk of malignancy is cytologic evaluation of fine-ne...
Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. P...
The tumor immune microenvironment(TIME)of colorectal cancer contains indicators of unique therapeutic outcomes for each cancer patient. Deep learning-...
PURPOSE: Pancreatic cancer is expected to be the second leading cause of cancer-related deaths worldwide within few years. Most patients are not diagn...
Renal cell carcinoma (RCC) accounts for more than 90% of cases of malignant kidney tumors and represents 2-3% of all malignancies worldwide. Clear cel...
PURPOSE: Most individuals with a hereditary cancer syndrome are unaware of their genetic status to underutilization of hereditary cancer risk assessme...
Background Prior chest CT provides valuable temporal information (eg, changes in nodule size or appearance) to accurately estimate malignancy risk. Pu...
PURPOSE: Quantifying treatment response to gastroesophageal junction (GEJ) adenocarcinomas is crucial to provide an optimal therapeutic strategy. Rout...
Widespread interest in artificial intelligence (AI) in health care has focused mainly on deductive systems that analyze available real-world data to d...
Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis ...
Atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS) are relatively common breast lesions on the same spectrum of disease. Atypical d...