Latest AI and machine learning research in oncology/hematology for healthcare professionals.
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the CycleGAN, Pix2pix and U-Net models were used to generate the sCT images. The Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Peak Signal to Nois...
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classified by machine learning algorithms in patients with early stage ovarian cancer, which has rarely been reported.
OBJECTIVE: We aim to present a case of a 43-year-old patient dia-gnosed with cervical adenocarcinoma in the 15th week of pregnancy, who underwent robo...
BACKGROUND: Cutaneous warts are common benign skin lesions caused by human papillomavirus. Various treatment options are available for these but immun...
BACKGROUND: Multiple viral warts represent a frustrating challenge for both patients and physicians. Management is difficult, primarily due to recalci...
INTRODUCTION: Our goal was to evaluate and compare the diagnostic utility of thyroid hormone withdrawal (THW) and recombinant thyroid-stimulating horm...
The combination of artificial intelligence (AI) technology and medicine is an important milestone in the development of modern medicine, which realize...
The recent accumulation of cancer genomic data provides an opportunity to understand how a tumor's genomic characteristics can affect its responses to...
BACKGROUND AND AIMS: Standardized and robust risk-stratification systems for patients with hepatocellular carcinoma (HCC) are required to improve ther...
For the existing medical image edge detection algorithm image reconstruction accuracy is not high, the fitness of optimization coefficient is low, res...
Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple or single lesions larger than 5 mm. In contrast to...
Horgan et al. described the first robotic-assisted transhiatal esophagectomy in 2003. Although there is debate regarding the oncologic appropriateness...
Initial results of the ROBOT, which randomized between robot-assisted minimally invasive esophagectomy (RAMIE) and open transthoracic esophagectomy (O...
To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning. The researchers collected 519 lu...
Dacarbazine (DTIC) is a first-line chemotherapy drug that is widely used in clinical practice for malignant melanoma. DTIC is metabolized by the liver...
Leukemia diagnosis based on bone marrow cell morphology primarily relies on the manual microscopy of bone marrow smears. However, this method is great...
PURPOSE OF REVIEW: This review aims to shed light on recent applications of artificial intelligence in urologic oncology.
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care pl...
Machine learning (ML) is entering many areas of society, including medicine. This transformation has the potential to drastically change medicine and ...
Tumor stage and grade, visually assessed by pathologists from evaluation of pathology images in conjunction with radiographic imaging techniques, have...