Biomedical Informatics Commons^™

Deep Learning Approaches For Cancer Prognosis Prediction Using Histopathological, Omics, And Clinical Data, Shuai Jiang

Dartmouth College Ph.D Dissertations

Accurate prediction of patient outcomes is crucial for shared clinical decision-making, treatment planning, and patients' psychological adjustment. Histopathological features of cancer, including tumor size, lymph node involvement, and metastasis, are commonly incorporated into survival prediction models, underscoring the prognostic value of whole slide images (WSIs). Concurrently, studies have highlighted the significance of omics data, such as transcriptomics, in providing valuable insights into cancer prognosis.

The emerging deep learning methods have brought new opportunities in biomedical informatics. Despite a growing body of studies on the application of deep learning methods for predicting prognosis using WSIs, the results are varied, primarily due …

Advancing Clinical Bacterial Diagnosis: Gram-Stained Whole-Slide Image Classification With Attention-Based Deep Learning, Jack Mcmahon

Computer Science Senior Theses

We introduce a new method for the classification of Gram-stained WSIs. As a test for the diagnosis of blood infections, Gram stains are highly relevant to informing patient treatment. Rapid analysis of Gram stains has been shown to be positively associated with better clinical outcomes, indicating the need for better tools to aid in automatic Gram stain analysis. To date, this area of research has been underexplored, with previous studies relying on the manual patch-level annotation of WSIs to generate training data. This is the first application of a transformer-based model to Gram-stain WSI classification, an approach that is far …

Genome-Scale Methylation Analysis In Blood And Tumor Identifies Immune Profile, Age Acceleration, And Dna Methylation Alterations Associated With Bladder Cancer Outcomes, Ji-Qing Chen

Dartmouth College Ph.D Dissertations

Bladder cancer patients receive frequent screening due to the high tumor recurrence rate (more than 60%). Nowadays, the conventional monitoring method relies on cystoscopy which is highly invasive and increases patient morbidity and burden to the health care system with frequent follow-up. As a result, it is urgent to explore novel markers related to the outcomes of bladder cancer. Immune profiles have been associated with cancer outcomes and may have the potential to be biomarkers for outcomes management. However, little work has been conducted to investigate the associations of immune cell profiles with bladder cancer outcomes. Here, I utilized the …

Uncovering The Role Of Fat-Infiltrated Axillary Lymph Nodes In Obesity-Related Diseases With Statistical And Machine Learning Analyses, Qingyuan Song

Dartmouth College Ph.D Dissertations

The link between obesity and pathogenesis is a complex and multifaceted area of research that is yet to be fully understood. Ample evidence exists to demonstrate the direct relationship between excessive internal fat and various health conditions such as cancer, and metabolic and cardiovascular diseases. The infiltration of ectopic fat into axillary lymph nodes, observable on breast cancer screening images, has been shown to be correlated with body mass index (BMI) in women undergoing screening. This study aimed to explore the relationship between fat-infiltrated axillary lymph nodes (FIN) and obesity-related diseases, with the goal of evaluating the clinical value of …