F. Martín-González

ORCID: 0000-0002-9365-3603
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About
Contact & Profiles
Research Areas
  • Respiratory Support and Mechanisms
  • Geological and Geophysical Studies Worldwide
  • Cardiac Arrest and Resuscitation
  • Emergency and Acute Care Studies
  • Trauma and Emergency Care Studies
  • Machine Learning in Healthcare
  • earthquake and tectonic studies
  • Anomaly Detection Techniques and Applications
  • Sepsis Diagnosis and Treatment
  • Geological and Tectonic Studies in Latin America
  • Airway Management and Intubation Techniques
  • Archaeological and Historical Studies
  • Trauma Management and Diagnosis
  • Time Series Analysis and Forecasting
  • Intensive Care Unit Cognitive Disorders
  • Medieval Architecture and Archaeology
  • Archaeological and Geological Studies
  • Nosocomial Infections in ICU
  • Autopsy Techniques and Outcomes
  • Antibiotics Pharmacokinetics and Efficacy
  • Chronic Obstructive Pulmonary Disease (COPD) Research
  • Antimicrobial Resistance in Staphylococcus
  • Non-Invasive Vital Sign Monitoring
  • Historical and socio-economic studies of Spain and related regions
  • Pneumonia and Respiratory Infections

Universidad de Salamanca
2010-2017

Complejo Hospitalario de Salamanca
2014-2015

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Despite the frequent use of vancomycin in intensive care unit (ICU) patients, few studies aimed at characterizing population pharmacokinetics have been performed this critical population. Population coupled with pharmacodynamic analysis, order to optimize drug exposure and hence antibacterial effectiveness, has little applied these specific patients. STUDY ADDS Our model characterized pharmacokinetic profile adult ICU higher distribution volume...

10.1111/j.1365-2125.2010.03679.x article EN British Journal of Clinical Pharmacology 2010-04-12

This paper addresses the problem of decision-making in relation to administration noninvasive mechanical ventilation (NIMV) intensive care units.Data mining methods were employed find out factors influencing success/failure NIMV and predict its results future patients. These artificial intelligence-based have not been applied this field spite good obtained other medical areas.Feature selection provided most influential variables NIMV, such as hours, PaCO2 at start, PaO2 / FiO2 ratio...

10.3414/me14-01-0015 article EN Methods of Information in Medicine 2015-04-30
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