Latest AI and machine learning research in chemotherapy for healthcare professionals.
Tumor cell nuclear size (NS) indicates malignant potential in breast cancer; however, its clinical s...
PURPOSE: Ovarian cancer patients with a Homologous Recombination Deficiency (HRD) often benefit from...
BACKGROUND: Accurate prediction of pathological complete response (pCR) and disease-free survival (D...
A brain tumor (BT) is considered one of the most crucial and deadly diseases in the world, as it aff...
PURPOSE: Toxicity to systemic cancer treatment represents a major anxiety for patients and a challen...
BACKGROUND: Hand hygiene is a critical component of infection prevention in healthcare settings. Inn...
PURPOSE: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colo...
OBJECTIVE: This study aims to establish a new prognostic index using machine learning models to pred...
BACKGROUND AND PURPOSE: Atypical meningiomas are prevalent intracranial tumors with varied prognoses...
BACKGROUND: To verify overall survival predictions made with residual convolutional neural network-d...
Artificial Intelligence (AI), especially Machine Learning (ML), has developed systems capable of per...
BACKGROUND: The demand for total knee arthroplasty (TKA) is increasing, yet postoperative nausea and...
Cytotoxicity is essential in drug discovery, enabling early evaluation of toxic compounds during scr...
Cognitive impairment in patients with moyamoya disease (MMD) manifests earlier than clinical symptom...
Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of loc...
Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, whic...
BACKGROUND: Treatment of locally advanced rectal cancer (LARC) involves neoadjuvant chemoradiotherap...
In modern medical imaging-assisted therapies, manual annotation is commonly employed for liver and t...
BACKGROUND: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-r...
OBJECTIVES: This study aimed to develop machine learning (ML) prediction models for identifying bloo...
Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decision...