Latest AI and machine learning research in oncology/hematology for healthcare professionals.
: PSMA PET is essential tool in the management of prostate cancer (PCa) patients in various clinical settings of disease. The tremendous growth of the implementation of radiomics and artificial intelligence (AI) in medical imaging techniques has led to an increasing interest in their application in prostate-specific membrane antigen (PSMA) PET. The aim of this article is to systemically review the...
Currently, the focus of intraoperative imaging in brain tumor surgery is beginning to shift to optical methods such as optical coherence tomography (OCT), Raman spectroscopy, confocal laser endomicroscopy (CLE), and fluorescence lifetime imaging (FLIM). Optical imaging technologies provide in vivo and real-time high-resolution images of tissues. "Optical biopsy" can be considered as an alternative...
Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating ta...
Accurate breast cancer prognosis helps clinicians in selecting optimal treatments, potentially improving patient survival. We tested whether combining...
The accurate preoperative staging of laryngeal squamous cell carcinoma (LSCC) provides valuable guidance for clinical decision-making. The objective o...
Colorectal cancer liver metastasis (CRLM) remains the leading cause of mortality among colorectal cancer (CRC) patients, with more than half eventuall...
While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic an...
Making an early diagnosis of cancer still in the early stages, when completely asymptomatic, is the challenge modern medicine has been setting for sev...
Immune checkpoint inhibitors (ICIs) have demonstrated significant clinical benefits in cancer treatment, but only a minority of patients exhibit favor...
Breast cancer liver metastasis (BCLM) presents a critical challenge in breast cancer treatment and has substantial epidemiological and clinical signif...
BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into several health care sectors, including medical imagin...
The application of AI in oncology has been limited by its reliance on large, annotated datasets and the need for retraining models for domain-specif...
EfficientNet models are convolutional neural networks optimized for parameter allocation by jointly balancing network width, depth, and resolution. ...
Early detection and accurate diagnosis are essential to improving patient outcomes. The use of convolutional neural networks (CNNs) for tumor detect...
BACKGROUND: Accurate estimation of treatment response can help clinicians identify patients who would potentially benefit from systemic therapy. This ...
INTRODUCTION: Presently, heavy particle ion radiation therapy is commonly utilized for the treatment of deep-seated malignancies, such as brain tumors...
Patients with head and neck cancer often present with complex challenges due to a substantial comorbidity burden, including substance use disorders, a...
Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provincial control sites, and one background site, were se...
PURPOSE: This study aims to create a deep learning (DL) model capable of accurately delineating the ventricles, and by extension, the periventricular ...
Recently, there has been tremendous interest on the use of large language models (LLMs) in radiology. LLMs have been employed for various applications...