Pathology

Machine learning models based on routine blood and biochemical test data for diagnosis of neurological diseases.

Globally, nervous system diseases are the leading cause of disability-adjusted life-years and the se...

A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions.

Gastric cancer, a significant global health concern, exhibits high morbidity and mortality, especial...

Refined prognostication of pathological complete response in breast cancer using radiomic features and optimized InceptionV3 with DCE-MRI.

BACKGROUND: Neoadjuvant therapy plays a pivotal role in breast cancer treatment, particularly for pa...

Re: Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review.

CellMet: Extracting 3D shape and topology metrics from confluent cells within tissues.

During development and tissue repair, cells reshape and reconfigure to ensure organs take specific s...

Incremental Learning-Enabled Fault Diagnosis of Dynamic Systems: A Comprehensive Review.

Effective fault diagnosis is crucial for maintaining the reliability and safety of industrial system...

Exosomal Liquid Biopsy for the Early Detection of Gastric Cancer: The DESTINEX Multicenter Study.

IMPORTANCE: Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide, prima...

Deep learning neural network of adenocarcinoma detection in effusion cytology.

OBJECTIVE: Cytologic examination, which confirms the presence or absence of malignant cells, detects...

[Preliminary exploration of the applications of five large language models in the field of oral auxiliary diagnosis, treatment and health consultation].

To evaluate the accuracy of the oral healthcare information provided by different large language mo...

Deep sensorless tracking of ultrasound probe orientation during freehand transperineal biopsy with spatial context for symmetry disambiguation.

BACKGROUND: Diagnosis of prostate cancer requires histopathology of tissue samples. Following an MRI...

Quantum Chemistry Calculation-Assisted Large-Scale Collision Cross Section Prediction Empowers Derivatization-Enhanced Multidimensional Metabolomics.

Derivatization-enhanced multidimensional metabolomics combined with ion mobility mass spectrometry w...

An interpretable machine learning model for preoperative prediction of renal mass malignancy.

OBJECTIVE: To develop and validate a predictive model for distinguishing benign and malignant renal ...

Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.

Despite the critical role of DNA methylation, clinical implementations harnessing its promise have n...

Sensitive Detection and Identification Method of Erythrocyte-like Cells upon Doxorubicin Induced Differentiation with Vibrational Techniques.

Altered differentiation of blood cell precursors and their clonal expansion occurs in various types ...

Radiomics meets transformers: A novel approach to tumor segmentation and classification in mammography for breast cancer.

ObjectiveThis study aimed to develop a robust framework for breast cancer diagnosis by integrating a...

The poverty of diagnostic essentialism: reimagining diagnosis in the age of artificial intelligence.

The pursuit of medical diagnosis has long been shaped by an epistemic framework that assumes disease...

Advancements in DNA methylation technologies and their application in cancer diagnosis.

DNA methylation is a common epigenetic modification that maintains the integrity of the DNA sequence...

CPN2 alleviates cryptorchidism by inhibiting the NF-κB pathway and regulating immune responses.

Cryptorchidism, a common male reproductive disorder characterized by undescended testes, is associat...

Glo-In-One-v2: holistic identification of glomerular cells, tissues, and lesions in human and mouse histopathology.

PURPOSE: Segmenting intraglomerular tissue and glomerular lesions traditionally depends on detailed ...

Radiomics with Machine Learning Improves the Prediction of Microscopic Peritumoral Small Cancer Foci and Early Recurrence in Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning model using ...

AFM-Based Deep Learning Decodes Human Macrophage Mechanophenotypes.

Macrophage polarization into inflammatory (M1) and repairing/healing (M2) functional phenotypes are ...