AI Medical Compendium Topic

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Antibodies, Monoclonal, Humanized

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Faradaic Impedimetric Immunosensor for Label-Free Point-of-Care Detection of COVID-19 Antibodies Using Gold-Interdigitated Electrode Array.

Biosensors
Label-free electrochemical biosensors have many desirable characteristics in terms of miniaturization, scalability, digitization, and other attributes associated with point-of-care (POC) applications. In the era of COVID-19 and pandemic preparedness,...

Completion of Pembrolizumab in Advanced Non-Small Cell Lung Cancer-Real World Outcomes After Two Years of Therapy (COPILOT).

Clinical lung cancer
BACKGROUND: Seminal trials with first-line pembrolizumab for metastatic non-small cell lung cancer (NSCLC) mandated a maximum two-years treatment. We describe real-world outcomes of a multi-site Australian cohort of patients who completed two-years o...

Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision o...

Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (AD) patients undergoing treatment with dupilumab. Stratifying patients based on the erythema course is crucial for elucidating heterogeneous phenotypes...

OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data.

Cellular oncology (Dordrecht, Netherlands)
PURPOSE: Pancreatic Ductal Adenocarcinoma (PDAC) remains a challenging disease due to its complex biology and aggressive behavior with an urgent need for efficient therapeutic strategies. To assess therapy response, pre-clinical PDAC organoid-based m...

Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA.

JCO precision oncology
PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) data and to improve the prediction of survival and disease progression, risk stratification, and tre...

Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Clinical pharmacology and therapeutics
Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine learning integration. We introduce a novel kinetics-machine learning (kML) model that integrates baseline markers, tumor kinetics, and four on-treatment...