Max Gordon

Max Gordon

Adjungerad Lektor | Docent
E-postadress: max.gordon@ki.se
Besöksadress: Entrévägen 2, 18257 Danderyd
Postadress: D1 Kliniska vetenskaper, Danderyds sjukhus, D1 Ortopedi, 182 88 Stockholm

Om mig

  • Jag är docent och överläkare i ortopedi på Danderyds sjukhus. Utöver
    mitt kliniska intresse har jag programmerat sen mitten på 90-talet. Jag har
    under åren arbetat med olika hobbyprojekt i ett stort antal
    programmeringsspråk där R är sannolikt språket som ligger närmast
    hjärtat, jag har suttit i Stockholm R useR Group [1]s styrelse sen 2013 och
    har fyra publicerade paket. Mitt mest populära paket, htmlTable [2], laddas
    hem mer än 100 000 gånger/månad. Du kan hitta alla mina open-source
    projekt på Github-repo [3]. Jag har också en forsknings blogg, G-Forge,
    [4]där jag försöker lägga upp saker och ting som jag tycker är
    intressant ur ett ortoped-forsknings-perspektiv.
    [1] http://www.meetup.com/StockholmR/
    [2] https://github.com/gforge/htmlTable
    [3] https://github.com/gforge
    [4] http://gforge.se/

Forskningsbeskrivning

  • Mina huvudsakliga forskningsintressen är närvarande epidemiologi och
    maskininlärning där jag varit med och startat Clinical AI Research-lab [1]
    (CAIR-lab) med inriktning på kliniskt applicerbar AI. Jag disputerade 2014
    på hur patientfaktorer påverkar olika utfall efter höftproteser. Det var
    ett fantastiskt kul samarbete med Svenska Höftprotesregistret [2] som väckt
    mitt intresse för statistik och ledde mig till maskininlärning. Idag
    arbetar jag framförallt med AI för att tolka röntgenbilder där vi letar
    efter mönster/mätningar som kan vägleda kliniker till den bästa
    behandlingen.
    [1] https://ki.se/kids/cair-lab
    [2] http://shpr.se/

Artiklar

Alla övriga publikationer

Forskningsbidrag

  • Swedish Research Council
    1 January 2023 - 31 December 2025
    Early diagnosis of cancer is key for improving patient outcomes, but cancers are hard to diagnose if patients present with unspecific symptoms. The principal objective of the MEDECA study is to identify a multi-analyte blood test that can detect and map cancer within a mixed population presenting with serious but unspecific symptoms. We are including 1.000 patients referred to the Diagnostic Center at Danderyd Hospital (DC DS), a multidisciplinary diagnostic center referral pathway. Blood samples are collected prior to a standardized and comprehensive cancer diagnostic work-up including an expanded panel of biochemical analyses and extensive imaging such as CT or MR investigations. In close international collaboration with world-leading scientists within the field of "liquid biopsy", the blood samples will be analyzed for a panel of novel and established blood biomarkers predicitve of an underlying cancer. These include markers of neutrophil extracellular traps, circulating tumor DNA, platelet mRNA profiling, affinity-based proteomics and nuclear resonance metabolomics. The diagnostic accuracy of the blood biomarkers with respect to cancer detection will be analyzed through machine learning, with the overarching goal to develop a multi-analyte blood test that can detect an occult cancer. This may lead to an earlier diagnosis, prompt cancer treatment and reduced morbidity and mortality. This would also lead to avoidance of unnecessary and costly investigations.
  • Swedish Research Council
    1 January 2022 - 31 December 2025
    Rational for conducting the study: The most commonly used treatment of displaced femoral neck fracture in the elderly is hemiarthroplasty which provides a reliable clinical result. Deep periprosthetic joint infection (PJI) is a severe complication associated with an increased morality and often leads to major and repeated reoperations. PJI has been reported to occur in 2-4% of hemiarthroplasties after fracture. The aim of the trial is to investigate whether the risk of PJI is reduced after the use of dual impregnated antibiotic laden bone cement.Study design: Register-based, cluster randomized controlled trial.Population: Number of patients: 7,312. Inclusion criteria: Patients aged ≥60 year, with a displaced femoral neck fracture and eligible for hemiarthroplasty according to local guidelines. Exclusion criteria: Previous inclusion of contralateral hip. Pathological or stress fracture of the femoral neck or fracture adjacent to a previous ipsilateral hip implant.Intervention: Dual-impregnated antibiotic laden bone cement.Control: Single-impregnated antibiotic laden bone cement.Outcome: Primary outcome variable is the incidence of PJI within one year. Secondary outcome variables include the occurrence of re-operations for any reason, mortality,and health care costs. Future benefit and clinical application: A reduction of PJI could decrease the morbidity and mortality of this elderly population and reduce the need for reoperations and antibiotic treatment.

Anställningar

  • Adjungerad Lektor, Kliniska vetenskaper, Danderyds sjukhus, Karolinska Institutet, 2024-2026

Examina och utbildning

  • Docent, ortopedi, Karolinska Institutet, 2022
  • Medicine Doktorsexamen, Institutionen för kliniska vetenskaper, Danderyds sjukhus, Karolinska Institutet, 2014

Nyheter från KI

Kalenderhändelser från KI