AIMC Topic: Sweden

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Hartmann's procedure vs abdominoperineal resection with intersphincteric dissection in patients with rectal cancer: a randomized multicentre trial (HAPIrect).

BMC surgery
BACKGROUND: The use of Hartmann's procedure in the old and frail and/or in patients with fecal incontinence is increasing, even though some data have reported high postoperative rates of pelvic abscesses. Abdominoperineal excision with intersphincter...

Designing a social and assistive robot for seniors.

Zeitschrift fur Gerontologie und Geriatrie
BACKGROUND: The development of social assistive robots is an approach with the intention of preventing and detecting falls among seniors. There is a need for a relatively low-cost mobile robot with an arm and a gripper which is small enough to naviga...

A class of joint models for multivariate longitudinal measurements and a binary event.

Biometrics
Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudin...

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool tr...

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

International journal of medical informatics
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), or pneumonia, which are often misdiagnosed. We aimed to create...

Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study.

Breast (Edinburgh, Scotland)
PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused ...

Machine learning explainability for survival outcome in head and neck squamous cell carcinoma.

International journal of medical informatics
BACKGROUND: Diagnosis and treatment of head and neck squamous cell carcinoma (HNSCC) induces psychological variables and treatment-related toxicity in patients. The evaluation of outcomes is warranted for effective treatment planning and improved dis...

Machine Learning to Improve Decision Support for Preventing Adverse Drug Events.

Studies in health technology and informatics
One approach to preventing adverse drug events (ADEs), such as harmful drug interactions, is the implementation of clinical decision support systems (CDSS). In an ongoing project, we are investigating the accuracy of the rule-based CDSS currently uti...