Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My NCBI Filters

Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2012 1
2015 1
2016 1
2019 1
2020 2
2021 3
2022 4
2023 2
2024 1

Text availability

Article attribute

Article type

Publication date

Search Results

12 results

Results by year

Filters applied: . Clear all
Page 1
Showing results for lasso rosen
Your search for Lasse Rosén retrieved no results
Risk Factors and Predictors of Mortality in Streptococcal Necrotizing Soft-tissue Infections: A Multicenter Prospective Study.
Bruun T, Rath E, Madsen MB, Oppegaard O, Nekludov M, Arnell P, Karlsson Y, Babbar A, Bergey F, Itzek A, Hyldegaard O, Norrby-Teglund A, Skrede S; INFECT Study Group. Bruun T, et al. Clin Infect Dis. 2021 Jan 27;72(2):293-300. doi: 10.1093/cid/ciaa027. Clin Infect Dis. 2021. PMID: 31923305 Free PMC article.
The impact of baseline factors and treatment on 90-day mortality was explored using Lasso regression. Whole-genome sequencing of bacterial isolates was used for emm typing and virulence gene profiling. ...
The impact of baseline factors and treatment on 90-day mortality was explored using Lasso regression. Whole-genome sequencing of bact …
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.
Fallerini C, Picchiotti N, Baldassarri M, Zguro K, Daga S, Fava F, Benetti E, Amitrano S, Bruttini M, Palmieri M, Croci S, Lista M, Beligni G, Valentino F, Meloni I, Tanfoni M, Minnai F, Colombo F, Cabri E, Fratelli M, Gabbi C, Mantovani S, Frullanti E, Gori M, Crawley FP, Butler-Laporte G, Richards B, Zeberg H, Lipcsey M, Hultström M, Ludwig KU, Schulte EC, Pairo-Castineira E, Baillie JK, Schmidt A, Frithiof R; WES/WGS Working Group Within the HGI; GenOMICC Consortium; GEN-COVID Multicenter Study; Mari F, Renieri A, Furini S. Fallerini C, et al. Hum Genet. 2022 Jan;141(1):147-173. doi: 10.1007/s00439-021-02397-7. Epub 2021 Dec 10. Hum Genet. 2022. PMID: 34889978 Free PMC article.
First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic …
First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An …
Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.
Zhou X, Chen Y, Ip FCF, Jiang Y, Cao H, Lv G, Zhong H, Chen J, Ye T, Chen Y, Zhang Y, Ma S, Lo RMN, Tong EPS; Alzheimer’s Disease Neuroimaging Initiative; Mok VCT, Kwok TCY, Guo Q, Mok KY, Shoai M, Hardy J, Chen L, Fu AKY, Ip NY. Zhou X, et al. Commun Med (Lond). 2023 Apr 6;3(1):49. doi: 10.1038/s43856-023-00269-x. Commun Med (Lond). 2023. PMID: 37024668 Free PMC article.
METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk deri …
METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk scor …
Development of a probability calculator for psychosis risk in children, adolescents, and young adults.
Moore TM, Calkins ME, Rosen AFG, Butler ER, Ruparel K, Fusar-Poli P, Koutsouleris N, McGuire P, Cannon TD, Gur RC, Gur RE. Moore TM, et al. Psychol Med. 2022 Oct;52(14):3159-3167. doi: 10.1017/S0033291720005231. Epub 2021 Jan 12. Psychol Med. 2022. PMID: 33431073 Free PMC article.
We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest, and statistical inference relief; and predicted future PS using ridge regression, random forest, and support vector machines. ...
We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest …
A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease.
Inglese M, Patel N, Linton-Reid K, Loreto F, Win Z, Perry RJ, Carswell C, Grech-Sollars M, Crum WR, Lu H, Malhotra PA; Alzheimer’s Disease Neuroimaging Initiative; Aboagye EO. Inglese M, et al. Commun Med (Lond). 2022 Jun 20;2:70. doi: 10.1038/s43856-022-00133-4. eCollection 2022. Commun Med (Lond). 2022. PMID: 35759330 Free PMC article.
For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). RESULTS: The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related path …
For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and select …
Sex differences in symptomatology of psychosis-risk patients and in prediction of psychosis.
Rosen M, Haidl TK, Ruhrmann S, Vogeley K, Schultze-Lutter F. Rosen M, et al. Arch Womens Ment Health. 2020 Jun;23(3):339-349. doi: 10.1007/s00737-019-01000-3. Epub 2019 Aug 28. Arch Womens Ment Health. 2020. PMID: 31485796
Sex-specific prediction models of psychosis were separately generated using Cox regressions with a LASSO operator. We found different small sex effects (0.10 < Rosenthal's r < 0.30) in the referral and in the converter sample. ...
Sex-specific prediction models of psychosis were separately generated using Cox regressions with a LASSO operator. We found different …
Training prediction models for individual risk assessment of postoperative complications after surgery for colorectal cancer.
Lin V, Tsouchnika A, Allakhverdiiev E, Rosen AW, Gögenur M, Clausen JSR, Bräuner KB, Walbech JS, Rijnbeek P, Drakos I, Gögenur I. Lin V, et al. Tech Coloproctol. 2022 Aug;26(8):665-675. doi: 10.1007/s10151-022-02624-x. Epub 2022 May 20. Tech Coloproctol. 2022. PMID: 35593971
Of 17,190 patients that received an anastomosis, 929 experienced anastomotic leakage (5.4%). Among the compared machine learning models, Lasso Logistic Regression performed best. The predictive model for complications had an area under the receiver operating characteristic …
Of 17,190 patients that received an anastomosis, 929 experienced anastomotic leakage (5.4%). Among the compared machine learning models, …
Predicting late radiation-induced xerostomia with parotid gland PET biomarkers and dose metrics.
Wilkie JR, Mierzwa ML, Casper KA, Mayo CS, Schipper MJ, Eisbruch A, Worden FP, El Naqa I, Viglianti BL, Rosen BS. Wilkie JR, et al. Radiother Oncol. 2020 Jul;148:30-37. doi: 10.1016/j.radonc.2020.03.037. Epub 2020 Apr 6. Radiother Oncol. 2020. PMID: 32311598 Free PMC article.
Multivariable analysis was applied for dose and PET features using penalized logistic regression for feature selection and generation of predictive models using the LASSO technique, and optimism bias was estimated by bootstrap resampling. ...
Multivariable analysis was applied for dose and PET features using penalized logistic regression for feature selection and generation of pre …
Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.
Silver M, Montana G; Alzheimer's Disease Neuroimaging Initiative. Silver M, et al. Stat Appl Genet Mol Biol. 2012 Jan 6;11(1):Article 7. doi: 10.2202/1544-6115.1755. Stat Appl Genet Mol Biol. 2012. PMID: 22499682 Free PMC article.
Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. No …
Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within path …
12 results