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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 remain underexplored. To address this issue, we analyzed the Gene Expression Omnibus (GEO) a…
FULLTEXT: machine parameter optimization -
Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis.
[BACKGROUND] Prostate cancer (PCa) is a leading cause of male cancer-related death globally. While the gut microbiota is linked to PCa, its genetic association remains unclear. [METHODS] We screened genetic instruments related to the gut m…
FULLTEXT: machine parameter optimization -
Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.
[OBJECTIVE] To construct and interpret a machine learning model for predicting overall survival in nonsurgical prostate cancer with bone metastases (PCBM). [METHODS] Data from 3,378 SEER database patients were utilized to develop machine l…
FULLTEXT: machine parameter optimization -
Trial Watch - bispecific T cell engagers and higher-order multispecific immunotherapeutics.
Over the past decades, cancer immunotherapy has evolved into clinical practice, with bispecific T cell engagers (TCEs) and other higher-order multispecific immunotherapeutics emerging as approaches for precision immune modulation. These eng…
FULLTEXT: machine parameter optimization -
Advances in natural killer cell immunotherapy for hematologic malignancies.
Natural killer (NK) cells are a unique subset of cytotoxic lymphocytes within the innate immune system. They play a pivotal role in antiviral and antitumor immunity. NK cell-based adoptive immunotherapy has advanced rapidly in recent years.…
FULLTEXT: machine parameter optimization -
Neutrophil extracellular trap-related genes in PTCL: identification, prognosis and drug interaction prediction via bioinformatics-machine learning.
[OBJECTIVE] This study aimed to identify neutrophil extracellular trap-related genes (NET-RGs), explore their prognostic significance, and predict drug interactions in peripheral T-cell lymphoma (PTCL). [METHODS] Differentially expressed N…
FULLTEXT: machine parameter optimization -
Cost-effectiveness analysis of atezolizumab and bevacizumab as first-line systemic therapy in unresectable hepatocellular carcinoma in Malaysia.
[AIM] This study aims to evaluate the cost-effectiveness of atezolizumab plus bevacizumab as first-line systemic therapy for unresectable hepatocellular carcinoma (uHCC) in Malaysia, compared with the current standard treatments in the Mala…
FULLTEXT: machine parameter optimization -
DA-LUNGNET: a multi-stage deep framework with adaptive attention for early detection of subcentimeter pulmonary nodules.
Early and reliable detection of subcentimeter pulmonary nodules remains a major bottleneck in low-dose CT-based lung cancer screening due to high miss rates, vascular-adhesion-induced false positives, and insufficient multi-scale feature fu…
FULLTEXT: machine parameter optimization -
Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease.
[BACKGROUND] Radiation pneumonitis (RP) is a serious complication in lung cancer patients with pre-existing interstitial lung disease (ILD) undergoing radiotherapy. Accurate risk stratification is crucial for individualized management. But …
FULLTEXT: machine parameter optimization -
Reforming the delivery of smoking cessation: a distributional cost-effectiveness analysis of providing smoking cessation as part of targeted lung cancer screening.
[BACKGROUND] Lung cancer is a leading cause of cancer death, and smoking-related disease is a major cause of health inequality in England, driven by increased prevalence of smoking in deprived areas. Integrating smoking cessation support in…
FULLTEXT: machine parameter optimization -
A data fusion deep learning approach for accurate organelle-based classification of cancer cells.
[PURPOSE] Microscopy-based cancer cell classification traditionally relies on cell-based morphological features, while subcellular organelle organization remains underutilized. Existing machine learning methods often require manual preproce…
FULLTEXT: machine parameter optimization -
A system dynamics modelling protocol to evaluate the impact of a health financing mechanism for breast cancer pharmacotherapies in Malaysia.
[INTRODUCTION] The rising cost of targeted breast cancer therapies challenges financial sustainability and equitable access in dual-tier health systems. In Malaysia, public cancer care is highly subsidized but budget constrained, shifting p…
FULLTEXT: machine parameter optimization -
Optimizing immunotherapy for head and neck squamous cell carcinoma: recent advances and future directions.
[BACKGROUND] Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy globally. Despite advancements in surgery, chemotherapy, and radiotherapy, the recurrence rate in advanced-stage HNSCC remains high, with a 5-…
FULLTEXT: machine parameter optimization -
Preclinical advances and mechanistic insights of CAR-T therapy for acute myeloid leukemia: from target iteration to microenvironment regulation.
[INTRODUCTION] Relapsed/refractory acute myeloid leukaemia (AML) carries a dismal prognosis, primarily due to profound biological heterogeneity and the scarcity of effective targeted therapies. Chimeric antigen receptor T (CAR-T) cell thera…
FULLTEXT: machine parameter optimization -
Research progress on the molecular mechanisms of PD-1 and LAG-3 synergy in regulating T cell exhaustion and immunotherapy.
[BACKGROUND] PD-1 and LAG-3 are immune checkpoint molecules frequently co-expressed in the tumor microenvironment, where they synergistically drive T-cell exhaustion and immune escape. Dual blockade of these pathways represents a promising …
FULLTEXT: machine parameter optimization -
Oncolytic virus therapy for hepatocellular carcinoma: A bibliometric analysis of research landscapes, hotspots, and clinical transformation trends from 2000 to mid-2025.
This study aimed to systematically analyze the research status, hotspots, and trends of oncolytic virotherapy (OV) for hepatocellular carcinoma (HCC) from 2000 to mid-2025, scientifically predict future directions, facilitate clinical trans…
FULLTEXT: machine parameter optimization -
Artificial intelligence-assisted FTIR spectroscopy for hormone receptor subtyping in formalin-fixed breast Cancer tissues.
[BACKGROUND] Determination of estrogen receptor (ER) and progesterone receptor (PR) status is critical for breast cancer subtyping and guiding endocrine therapy. Although immunohistochemistry (IHC) remains the diagnostic gold standard, it i…
FULLTEXT: machine parameter optimization -
Emerging frontiers in cervical cancer diagnostics: Recent innovations in biosensors for HPV detection.
Cervical cancer (CC) is recognized as a significant health concern impacting females worldwide. The pathogenicity of CC is associated with human papillomavirus (HPV). Timely diagnosis, therefore, becomes imperative for reducing mortality an…
FULLTEXT: machine parameter optimization -
Smart graphene-enhanced ceramic material refractive index sensor simulation design developed for highly sensitive breast Cancer detection optimized with machine learning.
Based on the surface plasmon resonance (SPR) technique, the proposed biosensor is investigated as an SPR-based sensing platform for detecting breast cancer cells, specifically MCF-7 and MDA-MB-231 cells. Developed biosensor features an octa…
FULLTEXT: machine parameter optimization -
An advanced diagnostic framework for discriminating lung cancer tissue subtypes via the synergy of fourier transform infrared spectroscopy and random forest.
Accurate subtyping of lung cancer is essential for improving patient prognosis and enabling personalized treatment. However, current clinical techniques are often time-consuming and heavily dependent on the operator's subjective judgment an…
FULLTEXT: machine parameter optimization