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The linear inverse problem associated with the standard model for hyperspectral image recovery from CASSI measurements is considered. This is formulated as the minimization of an objective function which is the sum of a total variation regularizer and a least squares loss function. Standard first-order iterative minimization algorithms, such as ISTA, FISTA and TwIST, require as input the value of
Soil microbes play an important role in governing global processes such as carbon cycling, but it is challenging to study them embedded in their natural environment and at the single cell level due to the opaque nature of the soil. Nonetheless, progress has been achieved in recent years towards visualizing microbial activities and organo-mineral interaction at the pore scale, especially thanks to
Recent studies of selective auditory attention have demonstrated that neural responses recorded with electroencephalogram (EEG) can be decoded to classify the attended talker in everyday multitalker cocktail-party environments. This is generally referred to as the auditory attention decoding (AAD) and could lead to a breakthrough for the next-generation of hearing aids (HAs) to have the ability to
The use of deep learning for classification tasks has shown great potential in medical applications. In critical domains as such, it is of high interest to have trustworthy algorithms which are able to tell when a reliable assessment cannot be guaranteed. Hence, detecting out-of-distribution (OOD) samples is a crucial step towards building a safe classifier. Following a previous study, showing tha
Vid regeringsbildningar har flera länder ett system där det enligt så kallade investiturregler krävs en omröstning i parlamentet. I och med 1974 års regeringsform är detta fallet även i Sverige. I den jämförande analys av olika länder som genomförs i detta kapitel visar det sig att ett sådant system är känsligt för förändringar av partisystemet. En genomgång av alla statsministeromröstningar i Sve
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 an artificial intelligence (AI) diagnostic decision support tool to detect patients with AHF, eCOPD, and pneumonia among dyspneic adults at the beginn
Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer’s disease (AD). However, CSF biomarker concentrations may be influenced by non-disease related inter-individual variability. Here we use a data-driven approach to demonstrate the existence of in
We describe a deep learning method to read hand-written records from the 16th century. The method consists of a combination of a segmentation module and a Handwritten Text Recognition (HTR) module. The transformer-based HTR module exploits both language and image features in reading, classifying and extracting the position of each word on the page. The method is demonstrated on a unique historical
Medical research generates a large number of publications with the PubMed database already containing >35 million research articles. Integration of the knowledge scattered across this large body of literature could provide key insights into physiological mechanisms and disease processes leading to novel medical interventions. However, it is a great challenge for researchers to utilize this informa
Many patients with Parkinson's disease (PD) experiencing L-DOPA-induced dyskinesia (LID) receive adjunct treatment with dopamine agonists, whose functional impact on LID is unknown. We set out to compare temporal and topographic profiles of abnormal involuntary movements (AIMs) after L-DOPA dose challenges including or not the dopamine agonist ropinirole. Twenty-five patients with PD and a history
Nya studier visar att elever ofta ignorerar feedback. Samtidigt vet vi att feedback är centralt för lärande. För att förstå vad som händer måste vi betrakta feedback som en sammanhängande process i flera steg av uppmärksamhet, tolkning, förståelse och användning. Detta i motsats till en traditionell modell som endast betraktar den feedback som ges (input) och elevens motsvarande prestation (output
https://www.svet.lu.se/kajsa-hansson - 2025-12-18
Kursguide - Course Syllabus Fastställande Kursplanen är fastställd av Programnämnden för masterutbildningar 2019-05-15 att gälla från och med 2019-05-16, höstterminen 2019. Allmänna uppgifter Kursen ges på avancerad nivå inom masterprogrammet i medicinsk vetenskap. Undervisningsspråk: Engelska Kursens mål Medicinska fakulteten MEVN43, Kognitiv utveckling och förmåga hos barn ur ett tvärprofessione
https://www.lu.se/sites/www.lu.se/files/mevn43.pdf - 2025-12-18
We present a synchronized multisensory dataset for accurate and robust indoor localization: the Lund University Vision, Radio, and Audio (LuViRA) Dataset. The dataset includes color images, corresponding depth maps, inertial measurement unit (IMU) readings, channel response between a 5G massive multiple-input and multiple-output (MIMO) testbed and user equipment, audio recorded by 12 microphones,
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and Audio (LuViRA) dataset, where all the sensors are synchronized and measured in the same environment. Some of the challenges of using each specific sensor for in
Accurate labels are critical for deriving robust machine learning models. Labels are used to train supervised learning models and to evaluate most machine learning paradigms. In this paper, we model the accuracy and cost of a common weak labeling process where annotators assign presence or absence labels to fixed-length data segments for a given event class. The annotator labels a segment as "pres
Erik J Olsson i Utbildningsradion: "Filterbubblor skapas av våra hjärnor" Erik J Olsson i Utbildningsradion: "Filterbubblor skapas av våra hjärnor" Publicerad den 7 november 2024 Erik J Olsson, professor i teoretisk filosofi vid Filosofiska institutionen, intervjuades i Utbildningsradions vetenskapspodd Besserwisser. En vanlig föreställning är att sökmotorer anpassar sökresultat till användarens v
https://www.fil.lu.se/article/erik-j-olsson-i-utbildningsradion-filterbubblor-skapas-av-vaara-hjaernor/ - 2025-12-15
Early detection of breast cancer is important to reduce morbidity and mortality. Access to breast imaging is limited in low- and middle-income countries compared to high-income countries. This contributes to advance-stage breast cancer presentation with poor survival. Pocket-sized portable ultrasound device, also known as point-of-care ultrasound (POCUS), aided by decision support using deep learn
With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary staging. This study employed advancements in deep learning to comprehensively evaluate routine mammograms for preoperative lymph node metastasis prediction. Mammograms and clinicopathological data from 1265 cN0 T1-T2 breast cancer patients (primary surge
