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Topic: Diagnosis

Seminar
5 seminars
Job
1 job

The winter selection recruits doctoral researchers to investigate cancer mechanisms and improve diagnosis, treatment and prevention. Applications close on 19 October 2026 through the DKFZ online system. Research is interdisciplinary, including experimental and computational approaches. Programme positions awarded through the selection are funded by a DKFZ PhD employment contract for at least three years, approximately equivalent to 65% TVöD E13, with social-security contributions and no tuition fees. Review the recruiting groups, admission requirements and application handbook before submissio

Seminar · Artificial Intelligence

How AI is advancing Clinical Neuropsychology and Cognitive Neuroscience

Nicolas Langer · University of Zurich

Wed, May 17, 2023 · 16:00 UTC

This talk aims to highlight the immense potential of Artificial Intelligence (AI) in advancing the field of psychology and cognitive neuroscience. Through the integration of machine learning algorithms, big data analytics, and neuroimaging techniques, AI has the potential to revolutionize the way we study human cognition and brain characteristics. In this talk, I will highlight our latest scientific advancements in utilizing AI to gain deeper insights into variations in cognitive performance across the lifespan and along the continuum from healthy to pathological functioning. The presentation

Seminar · Electrophysiology

Diagnosing dementia using Fastball neurocognitive assessment

George Stothart · University of Bath

Wed, Apr 19, 2023 · 16:00 UTC

Fastball is a novel, fast, passive biomarker of cognitive function, that uses cheap, scalable electroencephalography (EEG) technology. It is sensitive to early dementia; language, education, effort and anxiety independent and can be used in any setting including patients’ homes. It can capture a range of cognitive functions including semantic memory, recognition memory, attention and visual function. We have shown that Fastball is sensitive to cognitive dysfunction in Alzheimer’s disease and Mild Cognitive Impairment, with data collected in patients’ homes using low-cost portable EEG. We are n

Seminar · Medical Imaging

AI for Multi-centre Epilepsy Lesion Detection on MRI

Sophie Adler

Wed, Mar 1, 2023 · 18:00 UTC

Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area wh

Seminar · Medicine

Second National Training Course on Sleep Medicine

Birgit Frauscher, MD, Brian Murray, MD, Ron Postuma, MD

Thu, Nov 18, 2021 · 03:30 UTC

Many patients presenting to neurology either have primary sleep disorders or suffer from sleep comorbidity. Knowledge on the diagnosis, differential diagnostic considerations, and management of these disorders is therefore mandatory for the general neurologist. This comprehensive course may serve to fulfill part of the preparation requirements for trainees seeking to complete the Royal College Examinations in Neurology. This training course is for R4 and R5 residents in Canadian neurology training programs as well as neurologists.

Seminar · Psychology

The problem of power in single-case neuropsychology

Robert McIntosh · University of Edinburgh

Thu, Apr 1, 2021 · 16:00 UTC

Case-control comparisons are a gold standard method for diagnosing and researching neuropsychological deficits and dissociations at the single-case level. These statistical tests, developed by John Crawford and collaborators, provide quantitative criteria for the classical concepts of deficit, dissociation and double-dissociation. Much attention has been given to the control of Type I (false positive) errors for these tests, but far less to the avoidance of Type II (false negative) errors; that is, to statistical power. I will describe the origins and limits of statistical power for case-contr

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