Oncology/Hematology

[Psilocybin in the setting of treatment-resistant unipolar depression: A case report].

BACKGROUND: Current antidepressants have shown certain limitations in the treatment of unipolar depression. Their long onset of action, interactions, and side effects are obstacles to achieving lasting remission of this prevalent, often chronic or recurrent, pathology. Faced with this clinical necessity, research efforts have intensified in recent years around psychedelic drugs, with a particular ...

Deep Learning and Radiomic Signatures Associated with Tumor Immune Heterogeneity Predict Microvascular Invasion in Colon Cancer.

RATIONALE AND OBJECTIVES: This study aims to develop and validate a deep learning radiomics signature (DLRS) that integrates radiomics and deep learning features for the non-invasive prediction of microvascular invasion (MVI) in patients with colon cancer (CC). Furthermore, the study explores the potential association between DLRS and tumor immune heterogeneity.

Optimizing Treatment for Depression in Primary Care Using Psychotherapy Versus Antidepressant Medication in a Low-Resource Setting: Protocol for the OptimizeD Randomized Controlled Trial.

Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. H...

Enhancing Label-Free Fluorescence Lifetime Imaging for Intraoperative Tumor Margin Delineation in Head and Neck Cancer using Data-Centric AI.

Precise intraoperative delineation of tumor margin is critical for maximizing resection completeness and minimizing recurrence in head and neck cancer...

Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.

Glioma is a highly malignant brain tumor with limited treatment options. We employed the Computational Analysis of Novel Drug Opportunities (CANDO) pl...

Liquid Biopsy: The Challenges of a Revolutionary Approach in Oncology.

Liquid biopsy has gained attention in oncology as a non-invasive diagnostic tool, offering valuable insights into tumor biology through the analysis o...

Interpretable machine learning model integrating contrast-enhanced CT environmental radiomics and clinicopathological features for predicting postoperative recurrence in lung adenocarcinoma: a retrospective pilot study.

PURPOSE: This study aims to develop an interpretable predictive model combining contrast-enhanced CT (CECT) radiomics features with clinicopathologica...

Innate immune cell barrier-related genes inform precision prognosis in pancreatic cancer.

INTRODUCTION: Pancreatic cancer (PC) remains a lethal malignancy with limited treatment options. The role of innate immune cell barrier-related genes ...

Immune-related gene risk model establishment and role of key gene FUCA1 in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare type of tumor closely associated with asbestos exposure. Increasing evidence shows that hig...

Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study.

OBJECTIVES: To develop a machine learning-based model to predict the relapse risk of Primary Autoimmune Haemolytic Anaemia (AIHA) after the last remis...

ESR Essentials: a step-by-step guide of segmentation for radiologists-practice recommendations by the European Society of Medical Imaging Informatics.

High-quality segmentation is important for AI-driven radiological research and clinical practice, with the potential to play an even more prominent ro...

Artificial intelligence in neuro-oncology: methodological bases, practical applications and ethical and regulatory issues.

Artificial Intelligence (AI) is transforming neuro-oncology by enhancing diagnosis, treatment planning, and prognosis prediction. AI-driven approaches...

Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.

In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sec...

Imputing single-cell protein abundance in multiplex tissue imaging.

Multiplex tissue imaging enables single-cell spatial proteomics and transcriptomics but remains limited by incomplete molecular profiling, tissue loss...

Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways.

Breast cancer is a complex and challenging disease to treat, and despite progress in combating it, drug resistance remains a significant hindrance. Dr...

Optical coherence tomography angiography as a tool for diagnosis and monitoring of sickle cell related eye disease: a systematic review and meta-analysis.

Sickle cell retinopathy (SCR) is an ocular manifestation of sickle cell disease (SCD). In SCR abnormal sickling of erythrocytes is associated with sig...

Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model.

BACKGROUND: Sarcopenia is a clinicopathological condition characterized by a decrease in muscle strength and muscle mass, playing a crucial role in th...

Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients.

INTRODUCTION: Global longitudinal strain (GLS) is an important prognostic indicator for predicting heart failure and cancer therapy-related cardiac dy...

Assessment of contour accuracy in head and neck replanning: Deep learning trained model compared with deformable image registration propagation technique.

Accurate contouring is crucial for optimal treatment outcomes, whether for nonadaptive radiotherapy with single images or adaptive radiotherapy (ART) ...

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal feature interaction-guided fusion (DL-MFIF) framework t...