Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Decision Making01:20

Decision Making

926
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
926
Decision Making: P-value Method01:09

Decision Making: P-value Method

6.8K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
6.8K
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

5.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.1K
Patient-centered Care01:13

Patient-centered Care

2.9K
Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
2.9K
Drug Dosing: Obese Patients01:21

Drug Dosing: Obese Patients

238
In the United States, obesity is a prominent concern. It is linked to heightened mortality rates due to increased occurrences of conditions such as hypertension, atherosclerosis, coronary artery disease, and diabetes compared to nonobese individuals. A patient is classified as obese if their actual body weight surpasses the ideal or desirable body weight by 20%, based on Metropolitan Life Insurance Company data. Ideal body weights consider average weights and heights for males and females...
238
Drug Dosing: Geriatric Patients01:15

Drug Dosing: Geriatric Patients

229
Elderly individuals encompass a diverse population with varying degrees of age-related physiological changes. Defining the elderly presents challenges, as the geriatric population is often arbitrarily categorized as individuals older than 65. However, many individuals in this group lead active and healthy lives, with an increasing number surpassing 85 years and falling into the older elderly category. Physiological changes associated with aging impact performance capacity and homeostatic...
229

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Optimized OF-Score- Therapy Prediction in Successfully Treated Patients With Osteoporotic Spine Fractures Using Minimal Clinically Important Difference.

Global spine journal·2026
Same author

Digital Health and Smart Technologies in Shoulder Arthroplasty: Emerging Tools and Clinical Implications.

Orthopedic research and reviews·2026
Same author

Influence of the Region of Injury on Risk of Mortality in Severely Injured Patients Stratified by Age: An Analysis of 98,481 Patients from the TraumaRegister DGU<sup>®</sup>.

Journal of clinical medicine·2026
Same author

Treatment and outcome of osteoporotic OF3 vertebral fractures: results from the prospective multicenter EOFTT study.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society·2026
Same author

The bisegmental Cobb angle in osteoporotic spine fractures: Does it influence treatment decision or functional outcome?

Brain & spine·2026
Same author

The Modified Spinal Instability Spondylodiscitis Score (mSISS): Adaptation and Validation of a Novel Classification System for Spinal Instability in Spondylodiscitis.

Global spine journal·2026
Same journal

[3D printing in fracture treatment : Current practice and best practice consensus].

Der Unfallchirurg·2022
Same journal

[3D printing in trauma surgery : Germany lags far behind].

Der Unfallchirurg·2022
Same journal

[Subtrochanteric fractures].

Der Unfallchirurg·2022
Same journal

[3D printing in the field of shoulder surgery].

Der Unfallchirurg·2022
Same journal

[New assessment recommendations for disability in private accident insurance, part 1 : An interdisciplinary consented approach-Basics].

Der Unfallchirurg·2022
Same journal

[Amputation techniques].

Der Unfallchirurg·2022
See all related articles

Related Experiment Video

Updated: Jan 23, 2026

Focused Assessment with Sonography for Trauma FAST Exam: Image Acquisition
07:18

Focused Assessment with Sonography for Trauma FAST Exam: Image Acquisition

Published on: September 22, 2023

8.5K

[Computer-assisted decision-making for trauma patients].

Georg Osterhoff1, Dominik Pförringer2, Julian Scherer3

  • 1Klinik und Poliklinik für Orthopädie, Unfallchirurgie und Plastische Chirurgie, Universitätsklinikum Leipzig, Liebigstr. 20, 04103, Leipzig, Deutschland. georg.osterhoff@medizin.uni-leipzig.de.

Der Unfallchirurg
|June 5, 2019
PubMed
Summary
This summary is machine-generated.

Computer-assisted decision-making systems can improve trauma patient care by predicting critical situations and suggesting interventions. Overcoming technological and regulatory hurdles is key for widespread adoption in trauma management.

Keywords:
AlgorithmDecision makingDigitalizationMachine learningTrauma

More Related Videos

Pseudofracture: An Acute Peripheral Tissue Trauma Model
10:08

Pseudofracture: An Acute Peripheral Tissue Trauma Model

Published on: April 18, 2011

15.2K
Direct Mouse Trauma/Burn Model of Heterotopic Ossification
07:01

Direct Mouse Trauma/Burn Model of Heterotopic Ossification

Published on: August 6, 2015

10.6K

Related Experiment Videos

Last Updated: Jan 23, 2026

Focused Assessment with Sonography for Trauma FAST Exam: Image Acquisition
07:18

Focused Assessment with Sonography for Trauma FAST Exam: Image Acquisition

Published on: September 22, 2023

8.5K
Pseudofracture: An Acute Peripheral Tissue Trauma Model
10:08

Pseudofracture: An Acute Peripheral Tissue Trauma Model

Published on: April 18, 2011

15.2K
Direct Mouse Trauma/Burn Model of Heterotopic Ossification
07:01

Direct Mouse Trauma/Burn Model of Heterotopic Ossification

Published on: August 6, 2015

10.6K

Area of Science:

  • Medical Informatics
  • Trauma Surgery
  • Clinical Decision Support

Background:

  • Trauma patient management involves complex, time-sensitive decisions, often leading to errors even in experienced teams.
  • Computer-assisted decision-making (CADM) systems offer potential by analyzing real-time patient data to predict critical events.
  • These systems can provide crucial guidance for managing trauma patients in emergency settings.

Purpose of the Study:

  • To review existing concepts and applications of CADM systems in trauma patient management.
  • To summarize the current literature on CADM in the context of trauma care.

Main Methods:

  • A narrative review of scientific literature published in German and English over the past 10 years.
  • Analysis of studies focusing on computer-assisted decision-making in trauma care.

Main Results:

  • Numerous CADM systems exist for trauma care, with studies demonstrating improved patient outcomes in preclinical, resuscitation, and intensive care settings.
  • Successful implementation requires overcoming information technology barriers and adapting systems to data protection regulations.
  • Large-scale, multicenter studies are needed for further validation.

Conclusions:

  • CADM holds significant potential to enhance the management of trauma patients.
  • Widespread implementation necessitates addressing technological challenges and legislative requirements.