Academic Articles & Research Papers

LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles

An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasin...

Integrating task-state electroencephalography and motor function for intelligent assessment of recovery status from prolonged disorders of consciousness

Abstract Background Accurately assessing recovery in patients with prolonged disorders of consciousness (PDoC) is essential for evaluating the therapeutic efficacy and optimizing clinical care. However, substantial individual variability an...

Machine learning-based diagnostic prediction of minimal change disease: model development study

Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...

Strategy in the Age of Artificial Intelligence

We argue that Artificial Intelligence (AI) will, in the very near future, have a profound impact on the conduct of strategy and will be disruptive of existing power balances. To do so, we review the psychological foundations of strategy and...

The Myth of Artificial Intelligence

Futurists are certain that humanlike AI is on the horizon, but in fact engineers have no idea how to program human reasoning. AI reasons from statistical correlations across data sets, while common sense is based heavily on conjecture. Erik...

Medical ethics considerations on artificial intelligence

Neurosurgery and artificial intelligence

Neurosurgeons receive extensive and lengthy training to equip themselves with various technical skills, and neurosurgery require a great deal of pre-, intra- and postoperative clinical data collection, decision making, care and recovery. Th...

3D holographic reconstruction and intraoperative navigation combined with CBL teaching in laparoscopic partial nephrectomy training for urology residents.

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a ...

Multilevel Cognitive Machine-Learning-Based Concept for Artificial Awareness: Application to Humanoid Robot Awareness Using Visual Saliency

As part of “intelligence,” the “awareness” is the state or ability to perceive, feel, or be mindful of events, objects, or sensory patterns: in other words, to be conscious of the surrounding environment and its interactions. Inspired by ea...

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

PERMEPSY: a multicentre, randomized, double-blind proof-of-concept trial of personalized metacognitive training for adults with psychosis — a study protocol

BackgroundWhile psychological interventions are effective at improving symptoms of psychosis, accessible, cost- and time-efficient treatments remain limited. Personalized medicine has emerged as a promising approach, tailoring interventions...

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...

Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets

Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily...

Representations and Benchmarking of Modern Visual SLAM Systems

Simultaneous Localisation And Mapping (SLAM) has long been recognised as a core problem to be solved within countless emerging mobile applications that require intelligent interaction or navigation in an environment. Classical solutions to ...

The role of artificial intelligence in achieving the Sustainable Development Goals

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation proces...

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need ...

Artificial intelligence for natural product drug discovery

Artificial intelligence: Implications for the future of work

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a smal...

BEAMSTER: Brain mEtAstases segMentation for STEreotactic Radiotherapy, A Retrospective MRI Dataset with Expert Segmentations.