Donor lymphocyte infusions after haploidentical stem cell transplantation with PTCY: A study on behalf of the EBMT cellular therapy & immunobiology working party.

Donor lymphocyte infusion (DLI) is a treatment option to prevent or treat relapse after allogeneic hematopoietic cell transplantation (HCT). We here report data for 173 patients who received one or multiple DLIs after haploidentical-HCT with post-transplant cyclophosphamide (PTCY) at 47 EBMT centers from 2009 to 2018. Indication for DLI was: prophylactic for 59 (34.

Performance of a Predictive Model for Long-Term Hemoglobin Response to Darbepoetin and Iron Administration in a Large Cohort of Hemodialysis Patients.

Anemia management, based on erythropoiesis stimulating agents (ESA) and iron supplementation, has become an increasingly challenging problem in hemodialysis patients. Maintaining hemodialysis patients within narrow hemoglobin targets, preventing cycling outside target, and reducing ESA dosing to prevent adverse outcomes requires considerable attention from caregivers. Anticipation of the long-term response (i.

A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data.

Background: The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain.

BELM: Bayesian extreme learning machine.

The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space.

An integrated framework for risk profiling of breast cancer patients following surgery.

Objective: An integrated decision support framework is proposed for clinical oncologists making prognostic assessments of patients with operable breast cancer. The framework may be delivered over a web interface. It comprises a triangulation of prognostic modelling, visualisation of historical patient data and an explanatory facility to interpret risk group assignments using empirically derived Boolean rules expressed directly in clinical terms.

The use of neural networks for predicting the result of endoscopic treatment for vesico-ureteric reflux.

Objective: To create an artificial neural network (ANN) to aid in predicting the results of endoscopic treatment for vesico-ureteric reflux (VUR).

Materials And Methods: During 1999-2001 we used endoscopic treatment in 261 ureteric units with VUR of all grades and causes. An ANN based on multilayer perceptron architecture was created using an 11 x 6 x 1 structure, taking the following as variables: the cause and grade of VUR, the patient's age and sex, the type of implanted substance and its volume, the number of treatments, the affected ureter, the endoscopic findings, and the type of cystography used.