Results 241 to 250 of about 273,871 (338)

Survival Outcomes of Esophageal Squamous Cell Carcinoma Patients Who Underwent Salvage Esophagectomy: A Literature Review and Results From Two High‐Volume Centers

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This study aimed to investigate survival outcomes, the efficacy of lymph node (LN) dissection, and recurrence patterns in 69 patients who underwent R0 salvage surgery for esophageal squamous cell carcinoma. Of note, abdominal LN metastases had a negative impact on survival in our series.
Kotaro Sugawara   +9 more
wiley   +1 more source

Integrating Aggregate Materials and Machine Learning Algorithms: Advancing Detection of Pathogen‐Derived Extracellular Vesicles

open access: yesAggregate, EarlyView.
Pathogen‐derived extracellular vesicle detection: theoretical insights and advanced methodologies: This review explores the theoretical foundations and practical applications of pEV detection, emphasizing the challenges and innovative strategies involving novel aggregate materials and machine learning for enhanced diagnostic accuracy.
Lihan Lai   +6 more
wiley   +1 more source

Development and Application of Organic Sonosensitizers in Cancer Therapy

open access: yesAggregate, EarlyView.
This review provides a comprehensive overview of organic sonosensitizers employed in cancer treatment, describing their underlying mechanisms and structure‐activity relationship in terms of sonodynamic therapy. The significance of nanotechnology and combination therapy with other oncological modalities (photothermal therapy, photodynamic therapy, etc.)
Yuhan Ding   +5 more
wiley   +1 more source

PAR2 promotes malignancy in lung adenocarcinoma. [PDF]

open access: yesAm J Transl Res
Wang B   +10 more
europepmc   +1 more source

A Case of Small Peripheral Lung Adenocarcinoma with Remarkable Invasion of Bronchial Submucosal Lymph Ducts.

open access: bronze, 1998
Ko Tsuji   +5 more
openalex   +2 more sources

iPRISM: Intelligent Predicting Response to Cancer Immunotherapy through Systematic Modeling

open access: yesAdvanced Intelligent Systems, EarlyView.
The Intelligent Predicting Response to cancer Immunotherapy through Systematic Modeling (iPRISM) model uses data from genes and immune responses to predict how well cancer patients will respond to immunotherapy. Tested on multiple cancer types, iPRISM shows higher accuracy compared to existing methods.
Yinchun Su   +7 more
wiley   +1 more source

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