Oncology/Hematology

A machine learning model utilizing Delphian lymph node characteristics to predict contralateral central lymph node metastasis in papillary thyroid carcinoma: a prospective multicenter study.

BACKGROUND: This study aimed to use artificial intelligence (AI) to integrate various radiological and clinical pathological data to identify effective predictors of contralateral central lymph node metastasis (CCLNM) in patients with papillary thyroid carcinoma (PTC) and to establish a clinically applicable model to guide the extent of surgery.

Identification of genomic alteration and prognosis using pathomics-based artificial intelligence in oral leukoplakia and head and neck squamous cell carcinoma: a multicenter experimental study.

BACKGROUND: Loss of chromosome 9p is an important biomarker in the malignant transformation of oral leukoplakia (OLK) to head and neck squamous cell carcinoma (HNSCC), and is associated with the prognosis of HNSCC patients. However, various challenges have prevented 9p loss from being assessed in clinical practice. The objective of this study was to develop a pathomics-based artificial intelligenc...

Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review.

PURPOSE: The current review examined the application of artificial intelligence (AI) and machine learning (ML) techniques in palliative care, specific...

F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

OBJECTIVE: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positro...

Analyzing Secondary Cancer Risk: A Machine Learning Approach.

OBJECTIVE: Addressing the rising cancer rates through timely diagnosis and treatment is crucial. Additionally, cancer survivors need to understand the...

Identification of a gene score related to antigen processing and presentation machinery for predicting prognosis in head and neck squamous cell carcinoma and its potential implications for immunotherapy.

BACKGROUND: Despite its crucial role in immune surveillance and cell survival of tumors, the significance of MHC antigen processing and presentation m...

Machine Learning-Based Pathomics Model Predicts Angiopoietin-2 Expression and Prognosis in Hepatocellular Carcinoma.

Angiopoietin-2 (ANGPT2) shows promise as prognostic marker and therapeutic target in hepatocellular carcinoma (HCC). However, assessing ANGPT2 express...

Exploring machine learning tools in a retrospective case-study of patients with metastatic non-small cell lung cancer treated with first-line immunotherapy: A feasibility single-centre experience.

BACKGROUND: Artificial intelligence (AI) models are emerging as promising tools to identify predictive features among data coming from health records....

LC-MS profiling and cytotoxic activity of Angiopteris helferiana against HepG2 cell line: Molecular insight to investigate anticancer agent.

Liver cancer is one of the most prevalent malignant diseases in humans and the second leading cause of cancer-related mortality globally. Angiopteris ...

Quantitative immunohistochemistry analysis of breast Ki67 based on artificial intelligence.

Breast cancer is a common malignant tumor of women. Ki67 is an important biomarker of cell proliferation. With the quantitative analysis, it is an imp...

Viscum album, as alternative and bridge to palliative chemotherapy in recurrent gallbladder cancer following laparoscopic radical cholecystectomy: a case report.

A 78-year-old female patient was initially treated with laparoscopic radical cholecystectomy for gallbladder cancer (pT2aN1M0, stage IIIB). The patien...

AI-Driven insights in pancreatic cancer imaging: from pre-diagnostic detection to prognostication.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the United States, largely due to its poor five-year su...

A novel artificial intelligence segmentation model for early diagnosis of bladder tumors.

OBJECTIVE: Despite cystoscopy plays an important role in bladder tumors diagnosis, it often falls short in flat cancerous tissue and minuscule satelli...

Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping.

Deep learning methods have been widely used for various glioma predictions. However, they are usually task-specific, segmentation-dependent and lack o...

Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection.

Artificial Intelligence (AI) models may fail or suffer from reduced performance when applied to unseen data that differs from the training data distri...

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features.

BACKGROUND AND PURPOSE: Timely identification of local failure after stereotactic radiotherapy for brain metastases allows for treatment modifications...

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But ...

Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.

Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the ...

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significa...

Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders.

Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a...