Oncology/Hematology

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, but the reasons behind invasion and the changes occurring in invasive areas are still not well understood. This study aimed to explore the morphological differences between invasive and non-invasive areas in early esophageal cancer specimens that have undergone endoscopic submucosal dissection (ESD)...

Validating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.

This study examined the characteristics of the broad model (KBP) through a complete open-loop evaluation of volumetric modulated arc therapy (VMAT) plans for prostate cancer in 30 patients at two institutions. KBP, trained using 561 prostate cancer VMAT plans from five institutions with different treatment protocols, was shared with two institutions. The institutions were not involved in the creat...

Optimizing the management of immune-related adverse events and survival in patients with thoracic cancer receiving immunotherapy through artificial intelligence (electronic patient-reported outcomes): The IMPATHI study.

INTRODUCTION: The lung cancer continues to be the primary cause of cancer-related deaths, despite significant advancements in treatment through the in...

[Impact of artificial intelligence on the evolution of clinical practices in oncology: Focus on language models].

Artificial intelligence (AI) is addressing many expectations for healthcare practitioners and patients in oncology. It has the potential to deeply tra...

Lymphoma triage from H&E using AI for improved clinical management.

AIMS: In routine diagnosis of lymphoma, initial non-specialist triage is carried out when the sample is biopsied to determine if referral to specialis...

Machine learning-assisted pattern recognition and imaging of multiplexed cancer cells a porphyrin-embedded dendrimer array.

Early cancer detection plays a vital role in improving the survival rate of cancer patients, underscoring the importance of developing cancer detectio...

The Depth Estimation and Visualization of Dermatological Lesions: Development and Usability Study.

BACKGROUND: Thus far, considerable research has been focused on classifying a lesion as benign or malignant. However, there is a requirement for quick...

A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms.

BACKGROUND: Aplastic anemia (AA) and myelodysplastic neoplasms (MDS) have similar peripheral blood manifestations and are clinically characterized by ...

Uncertainty-aware automatic TNM staging classification for [F] Fluorodeoxyglucose PET-CT reports for lung cancer utilising transformer-based language models and multi-task learning.

BACKGROUND: [F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical finding...

Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction.

The evaluation of drug-gene-disease interactions is key for the identification of drugs effective against disease. However, at present, drugs that are...

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

BACKGROUND: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose and increase the contrast enhancement of vascular a...

Improving the prediction of patient survival with the aid of residual convolutional neural network (ResNet) in colorectal cancer with unresectable liver metastases treated with bevacizumab-based chemotherapy.

BACKGROUND: To verify overall survival predictions made with residual convolutional neural network-determined morphological response (ResNet-MR) in pa...

Convolutional neural network-assisted Raman spectroscopy for high-precision diagnosis of glioblastoma.

Glioblastoma multiforme (GBM) is the most lethal intracranial tumor with a median survival of approximately 15 months. Due to its highly invasive prop...

Development of Deep Learning-Based Virtual Lugol Chromoendoscopy for Superficial Esophageal Squamous Cell Carcinoma.

BACKGROUND: Lugol chromoendoscopy has been shown to increase the sensitivity of detection of esophageal squamous cell carcinoma (ESCC). We aimed to de...

Attention-based Fusion Network for Breast Cancer Segmentation and Classification Using Multi-modal Ultrasound Images.

OBJECTIVE: Breast cancer is one of the most commonly occurring cancers in women. Thus, early detection and treatment of cancer lead to a better outcom...

Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.

OBJECTIVE: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optimal treatment planning and prognosis assessment. Th...

Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.

MicroRNAs (miRNAs), a class of small non-coding RNAs, play a vital role in regulating gene expression at the post-transcriptional level. Their discove...

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's health. Therefore, a timely and accurate diagnosis is ...

The establishment of PD-1 inhibitor treatment prognosis model based on dynamic changes of peripheral blood indexes in patients with advanced lung squamous cell carcinoma.

BACKGROUND: Unlike patients with lung adenocarcinoma, patients with lung squamous cell carcinoma (LUSC) do not derive significant benefits from target...

Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning.

BACKGROUND: Several studies indicate that smoking is one of the major risk factors for bladder cancer. Nicotine and its metabolites, the main componen...