Public Health & Policy

Ethics

Latest AI and machine learning research in ethics for healthcare professionals.

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NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search.

Deep neural network (DNN) deployment has been confined to larger hardware devices due to their expen...

Characterizing ssRNA and dsRNA electrophoretic behavior: empirical insights with neural network-aided predictions.

RNA-based therapeutics are currently at the forefront of the biopharmaceutical industry because of t...

Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.

Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for pre...

The fall and rise of Iruda: Reassembling AI through ethics-in-action.

This paper examines the case of Iruda, an AI chatbot launched in December 2020 by the South Korean s...

Graph Neural Network Driven Exploration of Non-Precious Metal Catalysts for Air-to-Ammonia Conversion.

Efficient ammonia production directly from the air with minimal energy consumption remains one of th...

A non-optically active lake salinity dataset by satellite remote sensing.

Water salinity characterizes the physicochemical properties of natural water, serving as an essentia...

A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference.

Medical image analysis using deep learning algorithms has become a basis of modern healthcare, enabl...

Prediction for the development of preeclampsia through non-invasive hemodynamics using machine learning, distinguishing early from late.

Preeclampsia (PE) and hypertensive disorders of pregnancy (HDP) are major contributors to maternal-f...

Non-invasive breath testing to detect colorectal cancer: protocol for a multicentre, case-control development and validation study (COBRA2 study).

BACKGROUND: Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom. The five...

A web-based prediction model for brain metastasis in non-small cell lung cancer patients.

BACKGROUND: Brain metastasis (BM) stands as a significant contributor to mortality among cancer pati...

Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.

The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessmen...

Advances in non-invasive diagnostic tools for endometriosis: A narrative review of the past ten years.

Endometriosis is a chronic condition defined by endometrium-like tissue outside the uterus, with sym...

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns.

The diverse nature and timing of a clubfoot relapse pose challenges for early detection. A relapsed ...

Thermodynamically consistent modeling of granular soils using physics-informed neural networks.

In recent years, data-driven approaches have gained considerable momentum in the scientific and engi...

Detecting and classifying the mechanics of cancer and non-cancer cells by machine learning algorithm.

The global burden of cancer has increased in recent years, posing a major public health challenge. G...

Non-Invasive Bedside Approaches for Assessing Microvascular Dysfunction.

Microvascular dysfunction is implicated in a range of acute and chronic conditions, ranging from car...

Employer liability in work accident: A machine learning application from the health and safety at work perspective in Colombia.

BackgroundWork accidents have been studied from the perspective of outcome indicators, quantifying t...

Teaching postsecondary students about the ethics of artificial intelligence: A scoping review protocol.

The field of AI carries inherent risks such as algorithmic biases, security vulnerabilities, and eth...

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