Other Cancers

A pioneering artificial intelligence tool to predict treatment outcomes in ovarian cancer via diagnostic laparoscopy.

Ovarian cancer is associated with high rates of patient mortality and morbidity. Laparoscopic assessment of tumor localization can be used for treatment planning in newly diagnosed high-grade serous ovarian carcinoma (HGSOC). While spread to multiple intra-abdominal areas is correlated with worse outcomes, whether other morphological tumor differences are also associated with patient outcomes is u...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study.

PURPOSE: Anti-PD-1 antibodies are widely used for cancer treatment, including in advanced renal cell carcinoma (RCC). However, the therapeutic response varies among patients. This study aimed to predict tumor response to nivolumab anti-PD-1 antibody treatment for advanced RCC by integrating genetic and clinical data using machine learning (ML).

Can ChatGPT provide parent education for oral immunotherapy?

BACKGROUND: Oral Immunotherapy (OIT) has exhibited great potential in the treatment of food allergy. However, there is no global consensus on best pra...

Breast Pathology Through the Digital Lens.

Digital pathology (DP) has significantly transformed breast pathology at Mount Sinai Hospital by enhancing diagnostic accuracy, collaboration, and edu...

Artificial Intelligence in bone Metastases: A systematic review in guideline adherence of 92 studies.

BACKGROUND: The last decade has witnessed a surge in artificial intelligence (AI). With bone metastases becoming more prevalent, there is an increasin...

A novel nomogram based on machine learning predicting overall survival for hepatocellular carcinoma patients with dynamic α‑fetoprotein level changes after local resection.

The principal aim of the present study was to develop and validate a nomogram predicting overall survival (OS) in patients with α-fetoprotein (AFP)-ne...

Role of artificial intelligence in advancing immunology.

Artificial intelligence (AI) has revolutionized various biomedical fields, particularly immunology, by enhancing vaccine development, immunotherapies,...

Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging.

Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection...

Leveraging TME features and multi-omics data with an advanced deep learning framework for improved Cancer survival prediction.

Glioma, a malignant intracranial tumor with high invasiveness and heterogeneity, significantly impacts patient survival. This study integrates multi-o...

Personalized therapeutic strategies and prognosis for advanced laryngeal squamous cell carcinoma: Insights from machine learning models.

PURPOSE: Despite the development of diverse treatment options, there has been an increase in mortality rates for laryngeal squamous cell carcinoma (LS...

Bald eagle-optimized transformer networks with temporal-spatial mid-level features for pancreatic tumor classification.

The classification and diagnosis of pancreatic tumors present significant challenges due to their inherent complexity and variability. Traditional met...

Machine learning technique-based four-autoantibody test for early detection of esophageal squamous cell carcinoma: a multicenter, retrospective study with a nested case-control study.

BACKGROUND: Autoantibodies represent promising diagnostic blood-based biomarkers that may be generated prior to the first clinically detectable signs ...

Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges.

Drug resistance is one of the main reasons for cancer treatment failure, leading to a rapid recurrence/disease progression of the cancer. Recently, ar...

The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm.

BACKGROUND: Palliative care is a key component of integrated care to improve care quality and reduce hospitalization costs for patients with chronic o...

Constructing a neural network model based on tumor-infiltrating lymphocytes (TILs) to predict the survival of hepatocellular carcinoma patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide, and early pathological diagnosis is crucial for formulat...

Clinical performance of a machine learning-based model for detecting lymph node metastasis in papillary thyroid carcinoma: A multicenter study.

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with a generally favorable prognosis, but lymph node metastasis (LNM) complicates t...

Bridging surgical oncology and personalized medicine: the role of artificial intelligence and machine learning in thoracic surgery.

Lung cancer remains the leading cause of cancer-related deaths globally, often detected in advanced stages with poor prognosis. While surgical resecti...

A comparative analysis of three graph neural network models for predicting axillary lymph node metastasis in early-stage breast cancer.

The presence of axillary lymph node metastasis (ALNM) in breast cancer patients is an important factor in deciding whether to have axillary surgery or...

Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based calculator.

BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer characterized by a high risk of lymph node metastasis (LNM). T...

Data-driven survival modeling for breast cancer prognostics: A comparative study with machine learning and traditional survival modeling methods.

Background This investigation delves into the potential application of data-driven survival modeling approaches for prognostic assessments of breast c...