Latest AI and machine learning research in chemotherapy for healthcare professionals.
Dengue causes approximately 10.000 deaths and 100Â million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in developing more effective strategies for control, diagnosis, and treatment. This study identifies relevant variables for the screening of dengue cases throu...
BACKGROUND: Pathological complete response (pCR) is an essential criterion for adjusting follow-up treatment plans for patients with breast cancer (BC). The value of the visual geometry group and long short-term memory (VGG-LSTM) network using time-series dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for pCR identification in BC is unclear.
Surfactants as synergistic agents are necessary to improve the stability and utilization of pesticides, while their use is often accompanied by unexpe...
PURPOSE: Developed and validated a deep learning radiomics nomogram using multi-phase contrast-enhanced computed tomography (CECT) images to predict n...
Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined patholo...
PURPOSE: This study aimed to assess tumor regression grade (TRG) in patients with rectal cancer after neoadjuvant chemoradiotherapy (NCRT) through a m...
BACKGROUND: Sintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal j...
Lung cancer is categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer. Of these, NSCLC accounts for approximat...
Platinum-based chemotherapy is the cornerstone treatment for female high-grade serous ovarian carcinoma (HGSOC), but choosing an appropriate treatment...
BACKGROUND: Primary pancreatic signet ring cell carcinoma (PSRCC), an extremely rare histologic variant of pancreatic cancer, has a poor prognosis. Th...
BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, wit...
BACKGROUND AND OBJECTIVES: Deep learning models (DLMs) are applied across domains of health sciences to generate meaningful predictions. DLMs make use...
BACKGROUND AND PURPOSE: species are well-known antifungal medicinal plants. (Apiaceae family) is a rarely investigated plant endemic to Iran. The pr...
BACKGROUND: Rectal tumors display varying degrees of response to total neoadjuvant therapy (TNT). We evaluated the performance of a convolutional neur...
Image-based deep learning models are used to extract new information from standard hematoxylin and eosin pathology slides; however, biological interpr...
Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for contr...
BACKGROUND: Although separate analysis of individual factor can somewhat improve the prognostic performance, integration of multimodal information int...
The cited article reports on a convolutional neural network trained to predict response to neoadjuvant chemotherapy from pre-treatment breast MRI scan...
BACKGROUND: The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering...
INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intra...