Latest AI and machine learning research in oncology/hematology for healthcare professionals.
The brain serves as the central command center for the nervous system in the human body and is made up of nerve cells known as neurons. When these nerve cells grow rapidly and abnormally, it can lead to the development of a brain tumor. Brain tumors are severe conditions that can significantly reduce a person's lifespan. Failure to detect or delayed diagnosis of brain tumors can have fatal conseq...
Artificial intelligence (AI) is rapidly transforming pediatric oncology by creating new means to improve the accuracy and efficacy of cancer diagnosis and treatment in children. This review critically examines current applications of AI technologies like machine learning (ML) and deep learning (DL) to the main types of pediatric cancers. However, the application of AI to pediatric oncology is pron...
PURPOSE: This bi-centric pilot study investigates the predictive value of pre-treatment [F]FDG PET/CT radiomics for assessing therapy response in prim...
Raman spectroscopy extracts rich biochemical information on a single cell, demonstrating significant potential for precise cancer identification. Whil...
Lung cancer remains a leading cause of global cancer mortality, demanding precise diagnostic tools for accurate subtype classification. This paper int...
BACKGROUND: Gastric cancer (GC) is the fifth most common malignant tumor worldwide. The peritoneum is a common site of metastasis in advanced GC, and ...
OBJECTIVE: Papillary thyroid carcinoma (PTC) has a high recurrence rate and lacks reliable diagnostic biomarkers. This study aims to identify robust t...
BACKGROUND: Artificial intelligence (AI) has revolutionized the field of gastroenterology, particularly in endoscopic and colonoscopic procedures. The...
Sepsis is a systemic inflammatory response syndrome that predisposes to severe lung infections (SeALAR) such as sepsis-associated acute lung injury (S...
OBJECTIVE: Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine learning approaches and big data analyses are viabl...
The integration and utilization of digital media, gamified learning strategies, and artificial intelligence (AI) are fundamentally transforming the la...
Cervical cancer is one of the most common cancers in women. Despite progress in prevention and success in early detection through cytologic screening ...
Genetic testing for pathogenic germline variants is critical for the personalized management of high-risk breast cancers, guiding targeted therapies a...
Artificial intelligence (AI) and machine learning (ML) are transforming cervical cancer research and offering advancements in diagnosis, prognosis, sc...
Due to imbalanced data values and high-dimensional features of lung cancer from CT scans images creates significant challenges in clinical research. T...
Bladder cancer is the fourth most common malignant tumor in men, with limited therapeutic biomarkers and heterogeneous responses to immunotherapy. Dis...
Differentiating follicular thyroid adenoma (FTA) from carcinoma (FTC) remains challenging due to similar histological features separate from invasion....
OBJECTIVE: The diagnosis of liver fibrosis is usually based on histopathological examination of liver puncture specimens. Although liver puncture is a...
BACKGROUND AND PURPOSE: The efficacy of immunotherapy in non-small cell lung cancer (NSCLC) is intricately associated with baseline PD-L1 expression r...
Sensitive detection of circulating tumor cells (CTCs) from peripheral blood can serve as an effective tool in the early diagnosis and prognosis of can...