Latest AI and machine learning research in oncology/hematology for healthcare professionals.
This study suggests a novel Acute Lymphoblastic Leukemia (ALL) diagnostic model, built solely on complete blood count (CBC) records. Using a dataset comprised of CBC records of 86 ALL and 86 control patients respectively, we identified the most ALL-specific parameters using a feature selection approach. Next, Grid Search-based hyperparameter tuning with a five-fold cross-validation scheme was adop...
Colorectal cancer (CRC) is one of the most common cancers worldwide, and its diagnosis and classification remain challenging for pathologists and imaging specialists. The use of artificial intelligence (AI) technology, specifically deep learning, has emerged as a potential solution to improve the accuracy and speed of classification while maintaining the quality of care. In this scoping review, we...
Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify disc...
Background Deep learning (DL) models can potentially improve prognostication of rectal cancer but have not been systematically assessed. Purpose To de...
Background Handcrafted radiomics and deep learning (DL) models individually achieve good performance in lesion classification (benign vs malignant) on...
INTRODUCTION: Prostate cancer (PCa) is a disease with a high prevalence and incidence worldwide. Screening has pursued the early diagnosis of this dis...
Leiomyosarcoma of urinary bladder (LMS-UB) is a highly malignant mesenchymal tumor, accounting for less than 0.5% of all bladder malignancies, with a ...
Early colorectal cancers refer to invasive cancers that have infiltrated into the submucosa without invading muscularis propria, and approximately 10%...
The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy in non-metastatic disease. However, the evaluation...
Colorectal cancer represents 4500 incidental cases in Switzerland per year, with an incidence increasing among the youngest patients. Technological in...
The journey to implement cancer genomic medicine (CGM) in oncology practice began in the 1980s, which is considered the dawn of genetic and genomic ca...
PURPOSE: Sensitive patient data cannot be easily shared/analyzed, severely limiting the innovative progress of research, specifically for marginalized...
PURPOSE: Efforts to use growing volumes of clinical imaging data to generate tumor evaluations continue to require significant manual data wrangling, ...
BACKGROUND: Development of a radiomics model for predicting lymph node metastasis status in rectal cancer patients based on 3-dimensional endoanal rec...
Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categories of digital pathology, biomarker development, an...
A 78-year-old male visited the referring hospital because of asymptomatic gross hematuria. The patient was diagnosed with bladder cancer, clinical sta...
BACKGROUND: The alteration of cerebrospinal fluid (CSF) in hematologic neoplasms is a poor prognostic marker. The characteristics of CSF are usually a...
The application of artificial neural network algorithm in pathological diagnosis of gastrointestinal malignant tumors has become a research hotspot. I...
UNLABELLED: Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resist...
One of the most effective approaches for identifying breast cancer is histology, which is the meticulous inspection of tissues under a microscope. The...