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An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL).
J Ultrasound
January 2025
, Costa Contina street n. 19, 66054, Vasto, Chieti, Italy.
Aim: o point out how novel analysis tools of AI can make sense of the data acquired during OL and OC diagnosis and treatment in an effort to help improve and standardize the patient pathway for these disease.
Material And Methods: ultilizing programmed detection of heterogeneus OL and OC habitats through radiomics and correlate to imaging based tumor grading plus a literature review.
Results: new analysis pipelines have been generated for integrating imaging and patient demographic data and identify new multi-omic biomarkers of response prediction and tumour grading using cutting-edge artificial intelligence (AI) in OL and OC.
Programmed Transformation of Osteogenesis Microenvironment by a Multifunctional Hydrogel to Enhance Repair of Infectious Bone Defects.
Adv Sci (Weinh)
January 2025
Orthopedic Institute, Department of Orthopedic Surgery, Medical 3D Printing Center, The First Affiliated Hospital, Changzhou Geriatric hospital, MOE Key Laboratory of Geriatric Diseases and Immunology, School of Basic Medical Sciences, Suzhou Medical College, Soochow University, Suzhou, Jiangsu, 215000, P. R. China.
Repair of infectious bone defects remains a serious problem in clinical practice owing to the high risk of infection and excessive reactive oxygen species (ROS) during the early stage, and the residual bacteria and delayed Osseo integrated interface in the later stage, which jointly creates a complex and dynamic microenvironment and leads to bone non-union. The melatonin carbon dots (MCDs) possess antibacterial and osteogenesis abilities, greatly simplifying the composition of a multifunctional material. Therefore, a multifunctional hydrogel containing MCDs (GH-MCD) is developed to meet the multi-stage and complex repair needs of infectious bone injury in this study.
View Article and Find Full Text PDFSmart Mesoporous Silica Nanoparticles in Cancer: Diagnosis, Treatment, Immunogenicity, and Clinical Translation.
Small
January 2025
The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou, 324000, China.
In cancer research and personalized medicine, mesoporous silica nanoparticles (MSNs) have emerged as a significant breakthrough in both cancer treatment and diagnosis. MSNs offer targeted drug delivery, enhancing therapeutic effectiveness while minimizing adverse effects on healthy cells. Due to their unique characteristics, MSNs provide targeted drug delivery, maximizing therapeutic effectiveness with minimal adverse effects on healthy cells.
View Article and Find Full Text PDFCutting-Edge Technologies of Meat Analogs: A Review.
Food Sci Anim Resour
January 2025
Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea.
This study was conducted to investigate the recent research trends of alternative protein foods being developed to replace traditional livestock foods and thus determine the current state of the technology and the potential for industrialization. The results of this study showed that the technology related to cultured meat has not yet reached industrialization. However, serum-free media development, technologies to improve culture efficiency, and technologies to improve taste and flavor are being researched.
View Article and Find Full Text PDFRobust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets.
Front Artif Intell
January 2025
Department of Computer and Automatic Control, Faculty of Engineering, Tanta University, Tanta, Egypt.
Introduction: Diabetes prediction using clinical datasets is crucial for medical data analysis. However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.
Methods: A novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed.
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