Medical image captioning via generative pretrained transformers.

The proposed model for automatic clinical image caption generation combines the analysis of radiological scans with structured patient information from the textual records. It uses two language models, the Show-Attend-Tell and the GPT-3, to generate comprehensive and descriptive radiology records. The generated textual summary contains essential information about pathologies found, their location, along with the 2D heatmaps that localize each pathology on the scans.

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.

Detecting Out-of-Distribution (OoD) data is one of the greatest challenges in safe and robust deployment of machine learning algorithms in medicine. When the algorithms encounter cases that deviate from the distribution of the training data, they often produce incorrect and over-confident predictions. OoD detection algorithms aim to catch erroneous predictions in advance by analysing the data distribution and detecting potential instances of failure.

Semiempirical Molecular Dynamics (SEMD) I: Midpoint-Based Parallel Sparse Matrix-Matrix Multiplication Algorithm for Matrices with Decay.

In this paper, we present a novel, highly efficient, and massively parallel implementation of the sparse matrix-matrix multiplication algorithm inspired by the midpoint method that is suitable for matrices with decay. Compared with the state of the art in sparse matrix-matrix multiplications, the new algorithm heavily exploits data locality, yielding better performance and scalability, approaching a perfect linear scaling up to a process box size equal to a characteristic length that is intrinsic to the matrices. Moreover, the method is able to scale linearly with system size reaching constant time with proportional resources, also regarding memory consumption.

Brain-computer interface based on generation of visual images.

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future.

[Synthesis of lipophilic tetraphenylporphyrins to design lipid-porphyrin ensembles].

Synthesis of symmetrical meso-arylsubstituted porphyrins with long chain hydrophobic substituents in the phenyl rings was achieved. The lipoporphyrins can be used to design supramolecular lipid ensembles of nanometer size.

Performance evaluation of existing de novo sequencing algorithms.

Two methods have been developed for protein identification from tandem mass spectra: database searching and de novo sequencing. De novo sequencing identifies peptide directly from tandem mass spectra. Among many proposed algorithms, we evaluated the performance of the five de novo sequencing algorithms, AUDENS, Lutefisk, NovoHMM, PepNovo, and PEAKS.

[The effect of antidepressants on the indices of the cardiointervalogram in intact rats and during the deprivation of paradoxical sleep].

The acute and chronic administration of antidepressants (amitriptyline, imipramine, befol) to rats led to the sympathetic influences of a cardiointervalogram as reduced cardiointervals and its increased amplitude and tension index. Imipramine was found to be effective in eliminating disadaptational abnormalities in cardiac performance, which promoted REM-sleep deprivation.