Oncology/Hematology

Explainable deep learning model WAL-net for individualized assessment of potentially reversible malnutrition in patients with cancer: a multicenter cohort study.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilize machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicenter cohort study including hospitalized oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined...

Identification of neural crest and melanoma cancer cell invasion and migration genes using high-throughput screening and deep attention networks.

BACKGROUND: Cell migration and invasion are well-coordinated in development and disease but remain poorly understood. We previously showed that the neural crest (NC) cell migratory wavefront shares a 45-gene panel with other cell invasion phenomena. To rapidly and systematically identify critical genes, we performed a high-throughput siRNA screen and statistical and deep learning analyses to deter...

Recurrence prediction of invasive ductal carcinoma from preoperative contrast-enhanced computed tomography using deep convolutional neural network.

Predicting the risk of breast cancer recurrence is crucial for guiding therapeutic strategies, including enhanced surveillance and the consideration o...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of survival outcomes based on treatment modalities, i....

Intratumoral and peritumoral radiomics based on 2D ultrasound imaging in breast cancer was used to determine the optimal peritumoral range for predicting KI-67 expression.

OBJECTIVES: Currently, radiomics focuses on intratumoral regions and fixed peritumoral regions, and lacks an optimal peritumoral region taken to predi...

Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer.

With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary stag...

Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer.

BACKGROUND: Accurate prediction of pathological complete response (pCR) to neoadjuvant chemotherapy has significant clinical utility in the management...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases (NDDs) have highlighted microglial dysfunction as...

Recent advancement in endoscopic diagnosis for risk stratification of gastric cancer.

Approximately 90% of cases of gastric cancer (GC) are caused by Helicobacter pylori infection, and screening esophagogastroduodenoscopy is effective f...

BIScreener: enhancing breast cancer ultrasound diagnosis through integrated deep learning with interpretability.

Breast cancer is the leading cause of death among women worldwide, and early detection through the standardized BI-RADS framework helps physicians ass...

Utilizing Immuno-Oncology registry data for enhanced non-small cell lung cancer treatment predictions.

OBJECTIVES: We aim to leverage more comprehensive phenotypic and genotypic clinical data to enhance the treatment response predictions.

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantation in refractory or relapsed acute myeloid leukem...

Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.

Neoantigens, which are tumor-specific peptides generated by malignant cells, can be presented to T cells to elicit immune responses. Owing to their tu...

Performance of AI Chatbots in Preliminary Diagnosis of Maxillofacial Pathologies.

BACKGROUND Artificial intelligence (AI) has shown significant potential in transforming healthcare by enabling accurate, data-driven decision-making. ...

AI Revolution in Radiology, Radiation Oncology and Nuclear Medicine: Transforming and Innovating the Radiological Sciences.

The integration of artificial intelligence (AI) into clinical practice, particularly within radiology, nuclear medicine and radiation oncology, is tra...

Transfer Learning With Adam Gold Rush Optimization for Endometrial Disease Classification Using Histopathological Image.

Uterine cancer also referred to as endometrial cancer, which significantly impacts the female reproductive organs. The early diagnosis increases the s...

Assessment of a Deep Learning Model Trained on Permanent Pathology for the Classification of Squamous Cell Carcinoma in Mohs Frozen Sections: Lessons Learned.

BACKGROUND: There is a scarcity of artificial intelligence models trained on frozen pathology. One way to expand the clinical utility of models traine...

Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.

Purpose To improve the generalizability of pathologic complete response (pCR) prediction following neoadjuvant chemotherapy using deep learning (DL)-...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast ...

Identification of a novel ferroptosis-induced immunogenic cell death related signature based on a machine learning framework in colorectal cancer.

BACKGROUND: Ferroptosis and immunogenic cell death play vital roles in colorectal cancer (CRC). The interplay between ferroptosis and immunogenic cell...