A comprehensive dataset and neural network approach for named entity recognition in the Uzbek language.

In this study, the authors presented a dataset for named entity recognition in the Uzbek language. The dataset consists of 2000 sentences and 25,865 words, and the sources were legal documents and hand-crafted sentences annotated using the BIOES scheme. The study is complemented by the fact that the authors demonstrated the applications of the created dataset by training a language model using the CNN + LSTM architecture, which achieves high accuracy in NER tasks, with an F1 score of 90.

Synthesis, structure, Hirshfeld surface analysis, and molecular docking studies of the cocrystal between the Cu(II) complex of salicylic acid and uncoordinated piracetam.

The cocrystal (or supramolecular complex) between the Cu(II) complex of salicylic acid and uncoordinated piracetam has been synthesized. Its structure is characterized by elemental analysis, FT-IR, UV-Vis spectroscopy, and X-ray crystallography. Spectroscopic methods confirm the formation of the metal complex, while X-ray crystallography establishes the molecular and crystal structure of the obtained compound.

Prediction of radiological decision errors from longitudinal analysis of gaze and image features.

Medical imaging, particularly radiography, is an indispensable part of diagnosing many chest diseases. Final diagnoses are made by radiologists based on images, but the decision-making process is always associated with a risk of incorrect interpretation. Incorrectly interpreted data can lead to delays in treatment, a prescription of inappropriate therapy, or even a completely missed diagnosis.

Centerline-guided reinforcement learning model for pancreatic duct identifications.

Purpose: Pancreatic ductal adenocarcinoma is forecast to become the second most significant cause of cancer mortality as the number of patients with cancer in the main duct of the pancreas grows, and measurement of the pancreatic duct diameter from medical images has been identified as relevant for its early diagnosis.

Approach: We propose an automated pancreatic duct centerline tracing method from computed tomography (CT) images that is based on deep reinforcement learning, which employs an artificial agent to interact with the environment and calculates rewards by combining the distances from the target and the centerline. A deep neural network is implemented to forecast step-wise values for each potential action.

8-Hy-droxy-quinolinium tri-chlorido-(pyridine-2,6-di-carb-oxy-lic acid-κ ,,')copper(II) dihydrate.

The title compound, (CHNO)[CuCl(CHNO)]·2HO, was prepared by reacting Cu acetate dihydrate, solid 8-hy-droxy-quinoline (8-HQ), and solid pyridine-2,6-di-carb-oxy-lic acid (Hpydc), in a 1:1:1 molar ratio, in an aqueous solution of dilute hydro-chloric acid. The Cu atom exhibits a distorted CuONCl octa-hedral geometry, coordinating two oxygen atoms and one nitro-gen atom from the tridentate Hpydc ligand and three chloride atoms; the nitro-gen atom and one chloride atom occupy the axial positions with Cu-N and Cu-Cl bond lengths of 2.011 (2) Å and 2.

Imaging the pancreas with photon-counting CT - A review of normal pancreatic anatomy.

Purpose: Compared to conventional energy integrating detector CT, Photon-Counting CT (PCCT) has the advantage of increased spatial resolution. The pancreas is a highly complex organ anatomically. The increased spatial resolution of PCCT challenges radiologists' knowledge of pancreatic anatomy.

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report.

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily.

Reinforcement learning-based anatomical maps for pancreas subregion and duct segmentation.

Background: The pancreas is a complex abdominal organ with many anatomical variations, and therefore automated pancreas segmentation from medical images is a challenging application.

Purpose: In this paper, we present a framework for segmenting individual pancreatic subregions and the pancreatic duct from three-dimensional (3D) computed tomography (CT) images.

Methods: A multiagent reinforcement learning (RL) network was used to detect landmarks of the head, neck, body, and tail of the pancreas, and landmarks along the pancreatic duct in a selected target CT image.

AI-initiated second opinions: a framework for advanced caries treatment planning.

Integrating artificial intelligence (AI) into medical and dental applications can be challenging due to clinicians' distrust of computer predictions and the potential risks associated with erroneous outputs. We introduce the idea of using AI to trigger second opinions in cases where there is a disagreement between the clinician and the algorithm. By keeping the AI prediction hidden throughout the diagnostic process, we minimize the risks associated with distrust and erroneous predictions, relying solely on human predictions.

Bis(8-hy-droxy-quinolinium) naphthalene-1,5-di-sulfonate tetra-hydrate.

The inter-action between 8-hy-droxy-quinoline (8HQ, CHNO) and naphthalene-1,5-di-sulfonic acid (HNDS, CHOS) in aqueous media results in the formation of the salt hydrate bis-(8-hy-droxy-quinolinium) naphthalene-1,5-di-sulfonate tetra-hydrate, 2CHNO·CHOS ·4HO. The asymmetric unit comprises one protonated 8HQ cation, half of an NDS dianion symmetrically disposed around a center of inversion, and two water mol-ecules. Within the crystal structure, these components are organized into chains along the [010] and [10] directions through O-H⋯O and N-H⋯O hydrogen-bonding inter-actions, forming a di-periodic network parallel to (101).

HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge.

Background And Purpose: To promote the development of auto-segmentation methods for head and neck (HaN) radiation treatment (RT) planning that exploit the information of computed tomography (CT) and magnetic resonance (MR) imaging modalities, we organized HaN-Seg: The Head and Neck Organ-at-Risk CT and MR Segmentation Challenge.

Materials And Methods: The challenge task was to automatically segment 30 organs-at-risk (OARs) of the HaN region in 14 withheld test cases given the availability of 42 publicly available training cases. Each case consisted of one contrast-enhanced CT and one T1-weighted MR image of the HaN region of the same patient, with up to 30 corresponding reference OAR delineation masks.

The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review.

Machine learning (ML) has revolutionized medical image-based diagnostics. In this review, we cover a rapidly emerging field that can be potentially significantly impacted by ML - eye tracking in medical imaging. The review investigates the clinical, algorithmic, and hardware properties of the existing studies.

vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images.

Background: Accurate and consistent contouring of organs-at-risk (OARs) from medical images is a key step of radiotherapy (RT) cancer treatment planning. Most contouring approaches rely on computed tomography (CT) images, but the integration of complementary magnetic resonance (MR) modality is highly recommended, especially from the perspective of OAR contouring, synthetic CT and MR image generation for MR-only RT, and MR-guided RT. Although MR has been recognized as valuable for contouring OARs in the head and neck (HaN) region, the accuracy and consistency of the resulting contours have not been yet objectively evaluated.

Synthesis, crystal structure and Hirshfeld surface analysis of di-aqua-bis-(-phenyl-enedi-amine-κ,')nickel(II) naphthalene-1,5-di-sulfonate.

The reaction of -phenyl-enedi-amine (OPD), sodium naphthalene1,5-di-sulfonate (NaNDS) and nickel sulfate in an ethanol-water mixture yielded the title compound, [Ni(OPD)(HO)]·NDS or [Ni(CHN)(HO)](CHOS). This salt consists of a complex [Ni(OPD)(HO)] cation with two bidentate OPD ligands and aqua ligands, and a non-coordinating NDS anion, which is the double-deprotonated form of HNDS. The Ni atom is situated at a center of inversion and exhibits a slightly tetra-gonally distorted {ON} octa-hedral coordination environment, with four shorter equatorial Ni-N bonds [2.

Prediction of pulp exposure before caries excavation using artificial intelligence: Deep learning-based image data versus standard dental radiographs.

Objectives: The objective was to examine the effect of giving Artificial Intelligence (AI)-based radiographic information versus standard radiographic and clinical information to dental students on their pulp exposure prediction ability.

Methods: 292 preoperative bitewing radiographs from patients previously treated were used. A multi-path neural network was implemented.

Synthesis, structure and Hirshfeld surface analysis of a coordination compound of cadmium acetate with 2-amino-benzoxazole.

A first coordination compound of 2-amino-benzoxazole (), namely, bis-(2-amino-benzoxazole-κ )bis-(acetato-κ ,')cadmium(II), [Cd(CHCOO)()], has been synthesized from ethanol solutions of Cd(CH(COO) and . In the monoclinic crystals with the space group 2/, the cadmium ions coordinate two neutral mol-ecules in a monodentate fashion through the oxazole N atom, while two acetate ligands are coordinated through the O atoms in a bidentate manner. The coordination polyhedron of the central ion is substanti-ally distorted octa-hedral.

Crystal structure and Hirshfeld surface analysis of 8-aza-niumylquinolinium tetra-chlorido-zincate(II).

The reaction of 8-amino-quinoline, zinc chloride and hydro-chloric acid in ethanol yielded the title salt, (CHN)[ZnCl], which consists of a planar 8-aza-n-ium-yl-quinolinium dication and a tetra-hedral tetra-chloro-zincate dianion. The 8-amino-quinoline moiety is protonated at both the amino and the ring N atoms. In the crystal, the cations and anions are connected by inter-molecular N-H⋯Cl and C-H⋯Cl hydrogen bonds, forming sheets parallel to (001).

Synthesis, crystal structure, Hirshfeld surface analysis and DFT study of the 1,1'-(buta-1,3-diyne-1,4-di-yl)bis-(cyclo-hexan-1-ol).

The title compound, CHO, was synthesized in order to obtain its guest-free form because 'wheel-and-axle'-shaped mol-ecules tend to crystallize from solutions as solvates or host-guest mol-ecules. It crystallizes in the monoclinic space group 2/ with two crystallographically non-equivalent mol-ecules, one situated on an inversion center and the other on a twofold axis. The rod-like 1,3-diyne fragments have the usual linear geometry.

Crystal structure and Hirshfeld surface analysis of two organic salts based on 1,3,4-thia-diazole derivatives.

During attempts to achieve inter-action between 2-amino-5-ethyl-1,3,4-thia-diazole with oxalyl chloride and 5-mercapto-3-phenyl-1,3,4-thia-diazol-2-thione with various diacid anhydrides, we obtained two co-crystals (organic salts), namely, 2-amino-5-ethyl-1,3,4-thia-diazol-3-ium hemioxalate, CHNS·0.5CO , (I), and 4-(di-methyl-amino)-pyridin-1-ium 4-phenyl-5-sulfanyl-idene-4,5-di-hydro-1,3,4-thia-diazole-2-thiol-ate, CHN ·CHNS , (II). Both solids were investigated by single-crystal X-ray diffraction and by Hirshfeld surface analysis.

A 178-clinical-center experiment of integrating AI solutions for lung pathology diagnosis.

In 2020, an experiment testing AI solutions for lung X-ray analysis on a multi-hospital network was conducted. The multi-hospital network linked 178 Moscow state healthcare centers, where all chest X-rays from the network were redirected to a research facility, analyzed with AI, and returned to the centers. The experiment was formulated as a public competition with monetary awards for participating industrial and research teams.

Changes in Radiologists' Gaze Patterns Against Lung X-rays with Different Abnormalities: a Randomized Experiment.

The workload of some radiologists increased dramatically in the last several, which resulted in a potentially reduced quality of diagnosis. It was demonstrated that diagnostic accuracy of radiologists significantly reduces at the end of work shifts. The study aims to investigate how radiologists cover chest X-rays with their gaze in the presence of different chest abnormalities and high workload.

HaN-Seg: The head and neck organ-at-risk CT and MR segmentation dataset.

Purpose: For the cancer in the head and neck (HaN), radiotherapy (RT) represents an important treatment modality. Segmentation of organs-at-risk (OARs) is the starting point of RT planning, however, existing approaches are focused on either computed tomography (CT) or magnetic resonance (MR) images, while multimodal segmentation has not been thoroughly explored yet. We present a dataset of CT and MR images of the same patients with curated reference HaN OAR segmentations for an objective evaluation of segmentation methods.

The efficiency of artificial intelligence methods for finding radiographic features in different endodontic treatments - a systematic review.

Objectives: To assess the efficiency of AI methods in finding radiographic features in Endodontic treatment considerations.

Material And Methods: This review was based on the PRISMA guidelines and QUADAS 2 tool. A systematic search was performed of the literature on cases with endodontic treatments, comparing AI algorithms (test) versus conventional image assessments (control) for finding radiographic features.

Synthesis, crystal structure and Hirshfeld surface analysis of -poly[[bis-(semicarbazide-κ ,)copper(II)]-μ-sulfato-κ :'].

The title polymer, [Cu(SO)(CHNO)] , has been synthesized from aqueous solutions of CuSO and semicarbazide. In the crystal structure, the Cu atoms are chelated by two neutral semicarbazide mol-ecules through the oxygen atom and a nitro-gen atom of the amino group. The remaining two positions of the Jahn-Teller-distorted octa-hedral coordination sphere are occupied by oxygen atoms of two sulfate anions in the axial positions.

2-Hy-droxy-ethyl-ammonium [2-(2,6-di-chloro-anilino)phen-yl]acetate monohydrate.

In the solid-state structure of the title compound derived from diclofenac, CHNO·CHClNO ·HO, the asymmetric unit contains one cation, one anion and a water mol-ecule, all in general positions. A complex network of hydrogen bonds is present in the crystal structure.