| 1. |
|
|
| 2. |
- Al-Abri, Ruqaiya, et al.
(författare)
-
Sub-Picosecond Carrier Dynamics Explored using Automated High-Throughput Studies of Doping Inhomogeneity within a Bayesian Framework
- 2023
-
Ingår i: Small. - 1613-6810. ; 19:33
-
Tidskriftsartikel (refereegranskat)abstract
- Bottom–up production of semiconductor nanomaterials is often accompanied by inhomogeneity resulting in a spread in electronic properties which may be influenced by the nanoparticle geometry, crystal quality, stoichiometry, or doping. Using photoluminescence spectroscopy of a population of more than 11 000 individual zinc-doped gallium arsenide nanowires, inhomogeneity is revealed in, and correlation between doping and nanowire diameter by use of a Bayesian statistical approach. Recombination of hot-carriers is shown to be responsible for the photoluminescence lineshape; by exploiting lifetime variation across the population, hot-carrier dynamics is revealed at the sub-picosecond timescale showing interband electronic dynamics. High-throughput spectroscopy together with a Bayesian approach are shown to provide unique insight in an inhomogeneous nanomaterial population, and can reveal electronic dynamics otherwise requiring complex pump-probe experiments in highly non-equilibrium conditions.
|
|
| 3. |
|
|
| 4. |
- Li, W, et al.
(författare)
-
Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL
- 2020
-
Ingår i: NPJ breast cancer. - : Springer Science and Business Media LLC. - 2374-4677. ; 6:1, s. 63-
-
Tidskriftsartikel (refereegranskat)abstract
- Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.
|
|
