Oncology/Hematology

Chemotherapy

Latest AI and machine learning research in chemotherapy for healthcare professionals.

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Systematic modeling of phenotypic drug response profiles inpatient-derived organoids

Patient-derived tumor organoids provide a physiologically relevant 3D disease model for preclinical ...

Rapid diagnosis of fever etiology using wearable temperature monitoring and machine learning

Introduction. Distinct temperature patterns have long been recognized to correlate with fevers of di...

Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction

In patients with breast cancer, pathological complete response (pCR) has been established as a clini...

Autonomous generation of decision-grade clinical evidence

Medical practice is bottlenecked by the slow production of high-quality clinical evidence. Despite p...

Effects of gabapentin on ongoing behaviors displayed by mice with chemotherapy neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and painful side effect of paclitaxel ...

Predicting Chemotherapy Response from Staging Laparoscopy Images

BackgroundFor patients with metastatic gastrointestinal cancers, chemotherapy resistance is a common...

OracleScreen-LILRB4: Machine Learning-Guided Discovery of Myeloid Immune Checkpoint Binders Validated in Patient-Derived Cells

The identification of small molecule modulators of immune checkpoint proteins remains a significant ...

Physics-Informed Neural Networks for Chemotherapy Pharmacokinetics: Benchmarking the Clinical Estimator and Exposing Parameter Identifiability

Physics-Informed Neural Networks (PINNs) are an attractive tool for partial-observation problems in ...

Prognostic performance of an AI-based recurrence risk model in clinically low-risk HR+/HER2- early breast cancer

Objective Accurate prognostication of recurrence risk in HR+/HER2- early breast cancer is central fo...

Self-Reported Side Effects Among Reddit Users Taking Unapproved Retatrutide

Gray-market retatrutide use is increasing, but patient safety experiences remain poorly characterize...

A Foundation Model for the Cancer Genome

Cancer is a disease of the genome, in which somatic mutations and copy-number alterations determine ...

Deep Learning Spatial Profiling of CD103+CD8+ T Cells and Survival in Rectal Cancer After Neoadjuvant Chemoradiotherapy

Background: CD8+ tumor-infiltrating lymphocytes (TILs) are established prognostic markers in colorec...

Interconnecting ADC Structure with Tumor Cell Biology with Multimodal Learning

Antibody-drug conjugates (ADCs) represent a significant advancement in cancer therapy, yet their dev...

Predicting Response to Neoadjuvant Chemotherapy in Ovarian Cancer from CT Baseline Using Multi-Loss Deep Learning

Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an...

Integrative Genomic, Single-Cell, and Functional Profiling of the CD48-CD244 Axis and NK-Cell Dysfunction in Multiple Myeloma

Multiple myeloma (MM) orchestrates immune evasion by subverting natural killer (NK) cell function. C...

Spatial remodeling of the urothelial carcinoma tumor microenvironment shapes response to neoadjuvant atezolizumab

The ABACUS study was a single arm, phase II trial evaluating neoadjuvant atezolizumab in operable ur...

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability

Chemotherapy dose optimization can be formulated as a dynamic treatment regime, requiring sequential...

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