Results 171 to 180 of about 571,106 (270)

Synergistic Effect of Ceftazidime-Avibactam with Aztreonam on Carbapenemase-Positive Klebsiella pneumoniae MBL+, NDM+ [Letter]

Infection and Drug Resistance
Ketaki Niranjan Pathak, Shital Shrikant Ghogale Department of Microbiology, Symbiosis Medical College for Women (SMCW), Symbiosis International (Deemed University) (SIU), Pune, Maharashtra, IndiaCorrespondence: Ketaki Niranjan Pathak, Department of ...
Pathak KN, Ghogale SS
doaj  

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

Medical Microbiology [PDF]

Journal of Clinical Pathology, 1985
openaire   +3 more sources

A Mixed Methods Pilot Study to Evaluate User Engagement with MedMicroMaps: A Novel Interactive E-learning Tool for Medical Microbiology. [PDF]

Med Sci Educ
Harrington J.
europepmc   +1 more source

The Effects of Supplemental Online Learning Aids on Student Performance and Student Engagement in Medical Microbiology

, 2014
Kimberly T. Murray
openalex   +1 more source

Medical microbiological approach to Archaea in oral infectious diseases

, 2013
Hiroshi Maéda, Kimito Hirai, Junji Mineshiba, Tadashi Yamamoto, Susumu Kokeguchi, Shogo Takashiba   +5 more
openalex   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

RanBALL: An Ensemble Machine Learning Framework for Accurate Subtype Identification of Pediatric B‐Cell Acute Lymphoblastic Leukemia

Advanced Intelligent Systems, EarlyView.
Here, we present RanBALL, an ensemble random projection‐based model for accurate and cost‐effective identification of B‐cell acute lymphoblastic leukemia subtypes is presented. By preserving patient‐to‐patient distance after dimension reduction by random projection and ensemble learning, RanBALL can facilitate the discovery of B‐ALL subtype‐specific ...
Lusheng Li, Hanyu Xiao, Xinchao Wu, Zhenya Tang, Joseph D. Khoury, Jieqiong Wang, Shibiao Wan   +6 more
wiley   +1 more source

Men, Microbes, and Medical Microbiologists: A Concise Pictorial History of Medical Microbiology and Infectious Diseases Han T. Siem [PDF]

, 2006
Jock Murray
openalex   +1 more source