Latest AI and machine learning research in oncology/hematology for healthcare professionals.
AI automated segmentations for radiation treatment planning (RTP) can deteriorate when applied in clinical cases with different characteristics than training dataset. Hence, we refined a pretrained transformer into a hybrid transformer convolutional network (HTN) to segment cardiac substructures lung and breast cancer patients acquired with varying imaging contrasts and patient scan positions. C...
The field of gastroenterology has experienced revolutionary advances over the past years, as flexible endoscopes have become widely accessible. In addition to enabling faster, less invasive, and more affordable treatment, flexible endoscopes have greatly improved the detection and endoscopic screening of malignancies and prevented many cancer-related deaths. The development and clinical applicatio...
Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cance...
Leukemia is a common type of blood cancer marked by the abnormal and uncontrolled proliferation and expansion of white blood cells. This anomaly impac...
Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patients' quality of life. This study aimed to establish...
PURPOSE: Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. C...
BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, placing a significant burden on healthcare systems globally. Developing high-pr...
INTRODUCTION: Artificial intelligence (AI) has the potential to significantly enhance workplace safety and mitigate occupational radiation exposure ri...
In this research work, we present our open-source Geant4-based Monte-Carlo simulation application, called RadField3D, for generating three-dimensional...
The scarcity of human biopsies available for drug testing is a paramount challenge for developing therapeutics, disease models, and personalized treat...
Photon-counting computed tomography (PCCT) marks a significant advancement over conventional Energy-integrating detector CT systems. This review highl...
Effective communication about breast and cervical cancers remains a persistent health challenge, with significant gaps in public understanding of ca...
Histopathological analysis is a cornerstone of cancer diagnosis, with Hematoxylin and Eosin (H&E) staining routinely acquired for every patient to v...
Cancer remains a leading cause of death worldwide, necessitating personalized treatment approaches to improve outcomes. Theranostics, combining mole...
PURPOSE: The management of chronic lymphocytic leukemia (CLL) has significantly improved with targeted therapies. However, many patients experience a ...
PURPOSE: The Cancer Genome Atlas (TCGA) project defined four distinct molecular subtypes of esophagogastric adenocarcinoma: microsatellite instable (M...
Prostate cancer is a leading cause of cancer-related deaths, with Gleason grading being key for assessing tumor aggressiveness. We propose a Graph Neu...
Digital pathology has made significant advances in tumor diagnosis and segmentation; however, image variability resulting from tissue preparation and ...
Molecular tumor boards present special challenges when it comes to information collection for case preparation. It is one of the most time-consuming t...
Chemotherapy toxicity can lead to acute hospital admissions, negatively impacting the healthcare system and patients' well-being. Machine learning (ML...