Oncology/Hematology

Partial Data and Total Pain: Clinical and Ethical Hazards of AI Applications in Palliative Care.

Medicine finds itself on the brink of an artificial intelligence (AI) revolution, promising to transform what it means to be human and thus what it means to encounter humans with serious illness. The character of such transformation in pain management remains yet to be determined, leaving open to what extent AI might exacerbate or resolve challenges confronting pain management. In this article, I ...

Taiwan Academy of Tumor Ablation (TATA) consensus on hepatocellular carcinoma ablation.

Hepatocellular carcinoma (HCC) ranks sixth in incidence and third in mortality worldwide, underscoring its public health burden. Ablation therapy is one of the curative treatments for early-stage HCC. With recent advances in systemic therapy, combining ablation with other modalities has demonstrated improved outcomes and has extended applicability to selected patients with intermediate and advance...

Longitudinal multisource clinical model for early lung cancer risk stratification and screening.

OBJECTIVES: Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current s...

Distinction between primary and metastatic mucinous ovarian carcinoma from histopathology images using deep learning.

Accurately distinguishing between primary and gastrointestinal metastatic mucinous ovarian carcinoma (MOC) is crucial but remains highly challenging. ...

Toxicogenomic Characterization of Perfluorooctanoic Acid-Associated Bladder Carcinogenesis.

OBJECTIVE: This study aims to bridge toxicological target prediction and bladder cancer transcriptomics by systematically identifying molecular signat...

NetG2P: Network-based genotype-to-phenotype transformation identifies key signaling crosstalk for prognosis in pan-cancer study.

BACKGROUND: Despite advances in whole-genome sequencing and identifying cancer-associated genetic alterations, understanding the influence of multiple...

Computational Fluid Dynamics Simulations to Inform Cancer Therapeutics.

Cancer therapies such as chemotherapy, radiopharmaceutical therapy, and transarterial embolization rely on effective drug or radiation delivery throug...

Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.

Increasing evidence suggests that Graves' disease (GD) may increase the risk of thyroid cancer (THCA), but diagnostic biomarkers associated with it re...

ALDH1L2 induces resistance to chemotherapy in small cell lung cancer by inhibiting ferroptosis.

Small cell lung cancer (SCLC) is known for its rapid growth and early metastasis, and SCLC patients are highly susceptible to chemoresistance. Studies...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Breaking resistance in BRAF-mutant Melanoma: Novel strategies and biomarkers for optimizing targeted therapies.

In metastatic melanoma with a BRAFV600 mutation, inhibitors of BRAF and MEK have improved survival. Resistance may be acquired through late genetic al...

Comparative Evaluation of Transfer Learning Models for Detecting Malignant Cells in Urinary Cytology.

AIMS AND OBJECTIVES: In the present paper, we compared the efficiency of six transfer learning models to detect malignant cells in urine cytology. We ...

Subclassification of Small Cell Lung Cancer Based on Gene Expression Signatures and Machine Learning.

Small-cell lung cancer (SCLC) is frequently subdivided into four molecular subtypes according to the activity of key transcription factors (TFs) NEURO...

Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.

Colorectal cancer (CRC) remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progre...

Experiences of Medical Imaging and Radiation Sciences students regarding an assessment based on an artificial intelligence-generated research concept paper.

INTRODUCTION: Artificial intelligence (AI) can complete tasks that once required human cognitive effort. As a result, assessments that traditionally m...

Integrative computational and experimental analysis identifies MEK-mediated carcinogenic effects of bisphenol A and diethyl phthalate in head and neck cancer.

We investigated the carcinogenic effects of four endocrine-disrupting chemicals-bisphenol A (BPA), diethyl phthalate (DEP), dimethyl phthalate (DMP), ...

End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study.

BACKGROUND: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet ...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS score genes has limited efficacy in differentiati...

A machine learning-based triage system for systemic EBV-positive T/NK cell lymphoproliferative diseases of childhood.

Systemic Epstein-Barr virus-positive (EBV-positive) T/NK cell lymphoproliferative diseases of childhood (sEBV+T/NK-LPD) are a spectrum of rare disease...

Integrating B-mode ultrasound radiomics and clinical variables to predict 26-week progression-free survival in advanced hepatocellular carcinoma under targeted immunotherapy.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality globally, with over 905,700 new cases and 830,200 de...