While breast cancer commonly presents at an early stage without axillary lymphatic spread, surgic... more While breast cancer commonly presents at an early stage without axillary lymphatic spread, surgical axillary staging by sentinel lymph node biopsy (SLNB) is routinely performed in all patients with clinically node-negative disease. This study presents the development and implementation of a personalized prediction tool for noninvasive lymph node staging (NILS) using artificial neural network algorithms. Routinely available clinical and tumor-related variables in the preoperative setting from a consecutive cohort of 800 breast cancer cases were included in model training and internal validation. The model was trained to handle missing data for the ten input variables, and the performance to distinguish benign/metastatic lymph nodes ranged from AUCs 0.72 to 0.74, with good calibration. The potential to abstain from axillary surgery was observed in 26% of patients using NILS for the prediction of nodal status and acknowledged a false negative rate of 10%, which is clinically accepted f...
Abstract—Patients with suspicion of acute coronary syn-drome (ACS) are difficult to diagnose and ... more Abstract—Patients with suspicion of acute coronary syn-drome (ACS) are difficult to diagnose and they belong to a very heterogenous group of patients. Some require immediate treatment while others, with only minor dis-orders, may be sent home. Detecting ACS patients ...
We derive novel algorithms for estimation of regularization parameters and for optimization of ne... more We derive novel algorithms for estimation of regularization parameters and for optimization of neural net architectures based on a validation set. Regularisation parameters are estimated using an iterative gradient descent scheme. Architecture optimization is performed by approximative combinatorial search among the relevant subsets of an initial neural network architecture by employing a validation set based optimal brain damage/surgeon (OBD/OBS) or a mean field combinatorial optimization approach. Numerical results with linear models and feed-forward neural networks demonstrate the viability of the methods
Bioinformatics/computer Applications in The Biosciences, 2002
The pairwise alignment of biological sequences obtained from an algorithm will in general contain... more The pairwise alignment of biological sequences obtained from an algorithm will in general contain both correct and incorrect parts. Hence, to allow for a valid interpretation of the alignment, the local trustworthiness of the alignment has to be quantified. We present a novel approach that attributes a reliability index to every pair of residues, including gapped regions, in the optimal alignment of two protein sequences. The method is based on a fuzzy recast of the dynamic programming algorithm for sequence alignment in terms of mean field annealing. An extensive evaluation with structural reference alignments not only shows that the probability for a pair of residues to be correctly aligned grows consistently with increasing reliability index, but moreover demonstrates that the value of the reliability index can directly be translated into an estimate of the probability for a correct alignment.
While breast cancer commonly presents at an early stage without axillary lymphatic spread, surgic... more While breast cancer commonly presents at an early stage without axillary lymphatic spread, surgical axillary staging by sentinel lymph node biopsy (SLNB) is routinely performed in all patients with clinically node-negative disease. This study presents the development and implementation of a personalized prediction tool for noninvasive lymph node staging (NILS) using artificial neural network algorithms. Routinely available clinical and tumor-related variables in the preoperative setting from a consecutive cohort of 800 breast cancer cases were included in model training and internal validation. The model was trained to handle missing data for the ten input variables, and the performance to distinguish benign/metastatic lymph nodes ranged from AUCs 0.72 to 0.74, with good calibration. The potential to abstain from axillary surgery was observed in 26% of patients using NILS for the prediction of nodal status and acknowledged a false negative rate of 10%, which is clinically accepted f...
Abstract—Patients with suspicion of acute coronary syn-drome (ACS) are difficult to diagnose and ... more Abstract—Patients with suspicion of acute coronary syn-drome (ACS) are difficult to diagnose and they belong to a very heterogenous group of patients. Some require immediate treatment while others, with only minor dis-orders, may be sent home. Detecting ACS patients ...
We derive novel algorithms for estimation of regularization parameters and for optimization of ne... more We derive novel algorithms for estimation of regularization parameters and for optimization of neural net architectures based on a validation set. Regularisation parameters are estimated using an iterative gradient descent scheme. Architecture optimization is performed by approximative combinatorial search among the relevant subsets of an initial neural network architecture by employing a validation set based optimal brain damage/surgeon (OBD/OBS) or a mean field combinatorial optimization approach. Numerical results with linear models and feed-forward neural networks demonstrate the viability of the methods
Bioinformatics/computer Applications in The Biosciences, 2002
The pairwise alignment of biological sequences obtained from an algorithm will in general contain... more The pairwise alignment of biological sequences obtained from an algorithm will in general contain both correct and incorrect parts. Hence, to allow for a valid interpretation of the alignment, the local trustworthiness of the alignment has to be quantified. We present a novel approach that attributes a reliability index to every pair of residues, including gapped regions, in the optimal alignment of two protein sequences. The method is based on a fuzzy recast of the dynamic programming algorithm for sequence alignment in terms of mean field annealing. An extensive evaluation with structural reference alignments not only shows that the probability for a pair of residues to be correctly aligned grows consistently with increasing reliability index, but moreover demonstrates that the value of the reliability index can directly be translated into an estimate of the probability for a correct alignment.
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Papers by Mattias Ohlsson