Oncology/Hematology

AI-based IsAb2.0 for antibody design.

Therapeutic antibody design has garnered widespread attention, highlighting its interdisciplinary importance. Advancements in technology emphasize the critical role of designing nanobodies and humanized antibodies in antibody engineering. However, current experimental methods are costly and time-consuming. Computational approaches, while progressing, faced limitations due to insufficient structura...

ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network.

Cancer is a severe illness that significantly threatens human life and health. Anticancer peptides (ACPs) represent a promising therapeutic strategy for combating cancer. In silico methods enable rapid and accurate identification of ACPs without extensive human and material resources. This study proposes a two-stage computational framework called ACP-CapsPred, which can accurately identify ACPs an...

Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.

Community-based palliative care is a useful, but underutilized service to support seriously ill older adults to remain safely at home and improve qual...

Machine Learning-Based Prediction Models of Mortality for Intensive Care Unit Patients Using Nursing Records.

This study aimed to develop ICU mortality prediction models using a conceptual framework, focusing on nurses' concerns reflected in nursing records fr...

Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging

Colorectal polyps are generally benign alterations that, if not identified promptly and managed successfully, can progress to cancer and cause affec...

Applications of artificial intelligence for machine- and patient-specific quality assurance in radiation therapy: current status and future directions.

Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, e...

[Preoperative Evaluation of Cervical Lymph Node Metastasis in Patients With Hashimoto's Thyroiditis Combined With Thyroid Papillary Carcinoma Using Machine Learning and Radiomics-Based Features: A Preliminary Study].

OBJECTIVE: To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyroid tumors in patients with Hashimoto's thyroiditi...

THGNCDA: circRNA-disease association prediction based on triple heterogeneous graph network.

Circular RNAs (circRNAs) are a class of noncoding RNA molecules featuring a closed circular structure. They have been proved to play a significant rol...

Predicting drug synergy using a network propagation inspired machine learning framework.

Combination therapy is a promising strategy for cancers, increasing therapeutic options and reducing drug resistance. Yet, systematic identification o...

Design, Fabrication, and Characterization of a User-Friendly Microfluidic Device for Studying Liver Zonation-on-Chip (ZoC)

Liver zonation is a fundamental characteristic of hepatocyte spatial heterogeneity, which is challenging to recapitulate in traditional cell culture...

Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data

Deep learning holds immense promise for aiding radiologists in breast cancer detection. However, achieving optimal model performance is hampered by ...

Application of m6A regulators to predict transformation from myelodysplastic syndrome to acute myeloid leukemia via machine learning.

Myelodysplastic syndrome (MDS) frequently transforms into acute myeloid leukemia (AML). Predicting the risk of its transformation will help to make th...

Histopathological Image Classification with Cell Morphology Aware Deep Neural Networks

Histopathological images are widely used for the analysis of diseased (tumor) tissues and patient treatment selection. While the majority of microsc...

Multimodal contrastive learning for spatial gene expression prediction using histology images

In recent years, the advent of spatial transcriptomics (ST) technology has unlocked unprecedented opportunities for delving into the complexities of...

A 3D Pancreatic Cancer Model with Integrated Optical Sensors for Noninvasive Metabolism Monitoring and Drug Screening

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heter...

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

Whole slide imaging is routinely adopted for carcinoma diagnosis and prognosis. Abundant experience is required for pathologists to achieve accurate...

Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.

BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease ...

TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellula...

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

BACKGROUND: The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate t...

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis.

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Hist...