Latest AI and machine learning research in oncology/hematology for healthcare professionals.
The clinical potential of bispecific T cell engagers (BTEs) is limited by their short serum half-life and the complexity and cost of recombinant protein manufacturing. Currently, BTEs rely on external production and repeat dosing, limiting scalability and patient access. Here we present a synDNA platform that enables in vivo assembly and long-term secretion of bispecific antibodies directly from h...
BACKGROUND: Communication during serious illness is often complex, emotionally charged, and cognitively demanding, particularly for patients and families with limited health literacy, sensory impairments, or language barriers. Existing communication supports inadequately address diverse information-processing needs, underscoring the need for thoughtfully designed, technology-enabled interventions....
BACKGROUND: R-loops regulate genome stability and transcription, but their roles in uveal melanoma (UVM) are unclear. METHODS: A total of 1,185 R-loop...
BACKGROUND: While expression-based signatures inform adjuvant therapy in breast cancer (BC), no approved molecular biomarkers exist for the neoadjuvan...
In stereotactic body radiotherapy for bone metastases using the CyberKnife system, spinal anatomy is generally employed as the alignment reference. Ho...
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is the standard minimally invasive modality for mediastinal staging in no...
BACKGROUND: Sentinel node biopsy (SNB) provides pathological staging of the neck in T1/T2 node-negative oral squamous cell carcinoma (OSCC). Up to 85%...
Artificial intelligence (AI) is increasingly applied to biomedical research, but most current systems remain limited to specific tasks, data types, or...
PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification o...
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Machine learning (ML) may enable the noninvasive prediction of histopat...
Early liver metastasis is a major factor contributing to the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Single-cell RNA sequencing (sc...
Dioxins are persistent environmental pollutants and key components of the human exposome with established carcinogenic potential. As airborne toxicant...
The gut microbiota appears to play a critical role in modulating antitumor immune responses and influencing the efficacy of cancer immunotherapy drugs...
Clinical and radiological outcomes after Stereotactic radiosurgery (SRS) for lung cancer brain metastases are heterogeneous, and prescription dose sel...
Cancer immunotherapy has revolutionised oncology by utilising immune-mediated mechanisms to achieve durable anti-tumour responses and long-term clinic...
Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagn...
BACKGROUND: Artificial intelligence technology is being widely developed in dermatology. However, there remains a lack of comprehensive data analyzing...
INTRODUCTION: To compare the diagnostic performance of endoscopy-based deep learning (DL) algorithms with endoscopists of different experience levels ...
Identifying image features that associate strongly with diagnostic or prognostic classes in large-scale, multi-channel spatial imaging is challenging ...
INTRODUCTION: Online patient educational materials (PEMs) have poor readability, limiting their intended purposes in improving patient comprehension o...