Oncology/Hematology

Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine learning integration. We introduce a novel kinetics-machine learning (kML) model that integrates baseline markers, tumor kinetics, and four on-treatment simple blood markers (albumin, C-reactive protein, lactate dehydrogenase, and neutrophils). Developed for immune-checkpoint inhibition (ICI) in non-s...

A cutting-edge deep learning-and-radiomics-based ultrasound nomogram for precise prediction of axillary lymph node metastasis in breast cancer patients ≥ 75 years.

OBJECTIVE: The objective of this study was to develop a deep learning-and-radiomics-based ultrasound nomogram for the evaluation of axillary lymph node (ALN) metastasis risk in breast cancer patients ≥ 75 years.

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, Pu...

Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and co...

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of resea...

Cell recognition based on features extracted by AFM and parameter optimization classifiers.

Intelligent technology can assist in the diagnosis and treatment of disease, which would pave the way towards precision medicine in the coming decade....

Machine Learning-Assisted Decision Making in Orthopaedic Oncology.

» Artificial intelligence is an umbrella term for computational calculations that are designed to mimic human intelligence and problem-solving capabil...

Deep learning empowered breast cancer diagnosis: Advancements in detection and classification.

Recent advancements in AI, driven by big data technologies, have reshaped various industries, with a strong focus on data-driven approaches. This has ...

Smell cancer by machine learning-assisted peptide/MXene bioelectronic array.

Non-invasive detection of tumors is of utmost importance to save lives. Nonetheless, identifying tumors through gas analysis is a challenging task. In...

Machine learning-based autophagy-related prognostic signature for personalized risk stratification and therapeutic approaches in bladder cancer.

OBJECTIVE: Bladder cancer (BCa) is a highly lethal urological malignancy characterized by its notable histological heterogeneity. Autophagy has swiftl...

Nano fuzzy alarming system for blood transfusion requirement detection in cancer using deep learning.

Periodic blood transfusion is a need in cancer patients in which the disease process as well as the chemotherapy can disrupt the natural production of...

Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and mortality rate, not to mention the marked interindi...

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth ...

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.

BACKGROUND: Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherap...

Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer.

Cancer is a complex disease intrinsically associated with cellular processes and gene expression. With the development of techniques such as single-ce...

Multi-omics based artificial intelligence for cancer research.

With significant advancements of next generation sequencing technologies, large amounts of multi-omics data, including genomics, epigenomics, transcri...

AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis.

TumorPrism3D software was developed to segment brain tumors with a straightforward and user-friendly graphical interface applied to two- and three-dim...

Prognostic prediction model for salivary gland carcinoma based on machine learning.

Although rare overall, salivary gland carcinomas (SGCs) are among the most common oral and maxillofacial malignancies. The aim of this study was to de...

Evaluation of online chat-based artificial intelligence responses about inflammatory bowel disease and diet.

INTRODUCTION: The USA has the highest age-standardized prevalence of inflammatory bowel disease (IBD). Both genetic and environmental factors have bee...

F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.

PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using F-fluorodeoxyglucose (FDG) P...