Results 271 to 280 of about 4,106,951 (336)
SOX2, PIWI proteins, and MALAT1 - plasma-based emerging biomarkers for cancer detection and monitoring. [PDF]
Kldiashvili E+5 more
europepmc +1 more source
Seeing inside the Body Using Wearable Sensing and Imaging Technologies
This review explores wearable technologies for noninvasive internal health monitoring. It categorizes approaches into indirect sensing (e.g., bioelectrical and biochemical signals) and direct imaging (e.g., wearable ultrasound and EIT), highlighting multimodal integration and system‐level innovation toward personalized, continuous healthcare.
Sumin Kim+3 more
wiley +1 more source
Cancer stem cell biomarkers in locally advanced head and neck squamous cell carcinoma. [PDF]
Caballero-Borrego M+6 more
europepmc +1 more source
Editorial: Biomarkers and immunotherapy for genitourinary tumors
Zeyu Han, Jianzhong Ai
openaire +3 more sources
State‐of‐the‐Art, Insights, and Perspectives for MOFs‐Nanocomposites and MOF‐Derived (Nano)Materials
Different approaches to MOF‐NP composite formation, such as ship‐in‐a‐bottle, bottle‐around‐the‐ship and in situ one‐step synthesis, are used. Owing to synergistic effects, the advantageous features of the components of the composites are beneficially combined, and their individual drawbacks are mitigated.
Stefanos Mourdikoudis+6 more
wiley +1 more source
Synergizing Liquid Biopsy and Hybrid PET Imaging for Prognostic Assessment in Prostate Cancer: A Focus Review. [PDF]
Stracuzzi F+8 more
europepmc +1 more source
This article summarizes significant technological advancements in materials, photonic devices, and bio‐interfaced systems, which demonstrate successful applications for impacting human healthcare via improved therapies, advanced diagnostics, and on‐skin health monitoring.
Seunghyeb Ban+5 more
wiley +1 more source
Machine‐Learning‐Aided Advanced Electrochemical Biosensors
Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan+9 more
wiley +1 more source