Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, with early detection being critical to improving patient outcomes. Recent advancements in deep learning have shown promise in enhancing diagnostic accuracy, particularly through the use of Convolutional Neural Networks (CNNs). This study proposes the integration of Differential Augmentation (DA) with CNNs to address ...
BACKGROUND: Artificial intelligence (AI)-based imaging analysis and circulating tumor-associated DNA (ctDNA) are both being used diagnostically in HPV-driven oropharynx squamous cell carcinoma (HPV-OPSCC). We evaluated associations between AI-measured tumor burden and ctDNA.
The purpose of the study is to determine if artificial intelligence (AI) models could provide dietary recommendations to manage chemotherapy-induced n...
UNSTRUCTURED: Digital health interventions offer promise for scalable and accessible healthcare, but access is still limited by some participatory cha...
IntroductionUp to 60% of adults with metastatic colorectal cancer (mCRC) receiving combination cytotoxic chemotherapy may experience loss of skeletal ...
Lung cancer has been stated as one of the prevalent killers of cancer up to this present time and this clearly underlines the rationale for early diag...
Prostate cancer (PCa) requires improved diagnostic strategies beyond conventional imaging. This review aimed to evaluate the role of prostate-specific...
BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery as their primary form of treatment. However, studie...
Post-hepatectomy liver failure (PHLF) is a severe complication following liver surgery. We aimed to develop a novel, interpretable machine learning (M...
BACKGROUND: Advancements in diagnostic and therapeutic modalities for giant cell tumors of bone (GCTB) have introduced molecular and radiological tool...
OBJECTIVES: Superficial esophageal squamous cell carcinoma (ESCC) detection is crucial. Although narrow-band imaging improves detection, its effective...
Dipeptidyl peptidase-IV (DPP-IV) is a circulating blood biomarker that diagnose pancreatic and thyroid cancers, as well as type 2 diabetes. Although c...
OBJECTIVES: To establish a precise and efficient diagnostic framework for distinguishing medication-related osteonecrosis of the jaw, radiation-induce...
BACKGROUND AND OBJECTIVES: Prostate cancer is the most common form of cancer in the male population. While the survival rate is high, many patients un...
Cancer remains one of the leading causes of mortality worldwide, making early diagnosis and precise treatment crucial for enhancing patient survival r...
This project aimed to develop and evaluate an automated, AI-based, volumetric brain tumor MRI response assessment algorithm on a large cohort of patie...
Patients with cardioembolic stroke often undergo CT of the left atrial appendage (LAA), for example, to determine whether thrombi are present in the L...
Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous variant of breast cancer distinguished by a lack of targeted therapies, posing...
Building deep learning models that can rapidly segment whole slide images (WSIs) using only a handful of training samples remains an open challenge in...
BACKGROUND: To develop a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CECT) to assess the rat sarcoma (RAS) onc...