Academic Articles & Research Papers

Magnetic field reconstruction from proton radiography via physics-guided out-of-distribution filtering

Reconstructing multidimensional vector fields from path-integrated projection data is a fundamental challenge in high-energy-density physics, particularly when experimental sources exhibit spectral broadening and shot-to-shot jitter. We pre...

Molecular Biology and Biotechnology

One of the exciting aspects of being involved in the field of molecular biology is the ever-accelerating rate of progress, both in the development of new methodologies and the practical applications of these methodologies. This popular text...

Plasmodium vivax Transmission in Africa.

Malaria in sub-Saharan Africa has historically been almost exclusively attributed to Plasmodium falciparum (Pf). Current diagnostic and surveillance systems in much of sub-Saharan Africa are not designed to identify or report non-Pf human m...

Encyclopedia of public health

Comme quelqu'un pourroit dire de moy que j'ay seulement faict icy un amas de fleurs estrangeres, n'y ayant fourny du mien que le filet à les lier. "Essais", Livre III, Chapitre XIII Michel de MontaignePublic Health is defined as health prom...

Encyclopedia of Public Health

Comme quelqu'un pourroit dire de moy que j'ay seulement faict icy un amas de fleurs estrangeres, n'y ayant fourny du mien que le filet à les lier. "Essais", Livre III, Chapitre XIII Michel de MontaignePublic Health is defined as health prom...

Aligning machines with human values: opacity and ethical sustainability of AI

Abstract The increasingly rapid development of deep learning algorithms is radically transforming society. The potential of neural models is paving the way for the automation of areas previously unrelated to AI, from medical diagnostics to ...

MedScan, a natural language processing engine for MEDLINE abstracts

MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely us...

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

DIAGNOSTICS OF RUSTS AND SPOTTS OF WHEAT USING COMPUTER VISION METHODS

Purpose. To investigate the possibility of diagnosing yellow and brown rust (Puccinia striiformis f. sp. tritici West. Puccinia triticina f. sp. tritici Erikss), yellow spot (Pyrenophora tritici-repentis (Died.) Drechsler) on wheat leaves f...

The Patent Landscape of AI-Based Imaging Diagnostics for Osteoporosis: A Scoping Review.

Reframing decentralized diagnostics with a programmable multi-dimensional microfluidic system.

Computer Vision Malaria Diagnostic Systems—Progress and Prospects

Accurate malaria diagnosis is critical to prevent malaria fatalities, curb overuse of antimalarial drugs, and promote appropriate management of other causes of fever. While several diagnostic tests exist, the need for a rapid and highly acc...

An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders

Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...

An overview of deep learning in medical imaging focusing on MRI

What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...

Influence of a Deep Learning Noise Reduction on the CT Values, Image Noise and Characterization of Kidney and Ureter Stones

Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenu...

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability...

Towards Neural‐Network‐Based Optical Temperature Sensing of Semiconductor Membrane External Cavity Laser

Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...

Can Geopolitical Risk Improve the Forecasting of Thai Stock-Market Returns? Evidence from Econometrics and Machine-Learning Models

Geopolitical uncertainty may affect financial markets, but its incremental value for forecasting emerging-market stock returns remains unclear. Using monthly data from January 1990 to July 2026, this study compares ARIMA-GARCH and ARIMAX-GA...

Machine Learning for Detection and Diagnosis of Disease

Machine learning offers a principled approach for developing sophisticated, automatic, and objective algorithms for analysis of high-dimensional and multimodal biomedical data. This review focuses on several advances in the state of the art...

Interpretable machine learning to detect well integrity issues

The problem of timely and accurate evaluation of well integrity is becoming increasingly relevant in the context of mature field development, high wellstream water cut, and a growing number of old wells. For production casing diagnostics, g...