SolvedByAI

Papers

1,138 of 1,138 verified cases.

Search full text

Machine learning for continuous quantum error correction on superconducting qubits

Ian Convy, Haoran Liao, Song Zhang, Sahil Patel, William P. Livingston, Hồ Nam Nguyễn, Irfan A. Siddiqi, K. Birgitta Whaley

New Journal of Physics 2022 cited by 21

Physics & Astronomy Quantum Computing Algorithms and Architecture ai assisted importance 7/10 scale stated

Continuous quantum error correction must detect bit-flip errors from noisy, non-ideal syndrome measurements on superconducting qubits.

Details Source Open-access PDF model: Recurrent neural network

Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study

Manu Kohli, Arpan Kumar Kar, Anjali Bangalore, Prathosh AP

Brain Informatics 2022 cited by 51

Medicine & Health Autism Spectrum Disorder Research ai assisted importance 7/10 scale stated

Shortage of licensed ABA practitioners and subjective, non-data-driven planning limits timely autism treatment.

Details Source Open-access PDF model: patient similarity and collaborative filte...

Deep Learning for Bone Mineral Density and T-Score Prediction from Chest X-rays: A Multicenter Study

Yoichi Sato, Norio Yamamoto, Naoya Inagaki, Yusuke Iesaki, Takamune Asamoto, Tomohiro Suzuki, Shunsuke Takahara

Biomedicines 2022 cited by 84

Medicine & Health Bone health and osteoporosis research ai assisted importance 7/10 scale stated

Osteoporosis diagnosis and treatment are inadequate worldwide; the study predicts bone mineral density and T-score from routine chest X-rays.

Details Source Open-access PDF model: not stated in source

De novo design of high-affinity protein binders to bioactive helical peptides

Susana Vázquez Torres, Philip J. Y. Leung, Isaac D. Lutz, Preetham Venkatesh, Joseph L. Watson, Fabian Hink, Huu‐Hien Huynh, Andy Hsien-Wei Yeh et al.

bioRxiv (Cold Spring Harbor Laboratory) 2022 cited by 22

Biology & Life Sciences Protein Structure and Dynamics solved importance 7/10 scale stated

Designing proteins that bind short helical peptides (such as peptide hormones) with high affinity was an unmet challenge in de novo protein design.

Details Source Open-access PDF model: RF diffusion

Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images

Suzanne C. Wetstein, Vincent M. T. de Jong, Nikolas Stathonikos, Mark Opdam, Gwen M. H. E. Dackus, Josien P. W. Pluim, P. J. van Diest, Mitko Veta

Scientific Reports 2022 cited by 103

Medicine & Health AI in cancer detection ai assisted importance 7/10 scale stated

Pathologist grading of breast cancer shows significant inter-observer variation, and prior computer methods only work on selected tissue areas or need labor-intensive annotations.

Details Source Open-access PDF model: deep learning (specific architecture not s...

Power-grid stability predictions using transferable machine learning

Seong-Gyu Yang, Beom Jun Kim, Seung‐Woo Son, Heetae Kim

Chaos An Interdisciplinary Journal of Nonlinear Science 2021 cited by 22

Engineering & Materials Power System Optimization and Stability ai assisted importance 7/10 scale stated

Assessing the dynamic stability (frequency synchronization) of power grids via numerical simulation is computationally too expensive. The study asks whether machine learning can estimate node synchronization stability more cheaply and transferably.

Details Source Open-access PDF model: random forest, support vector machine, art...

Early Prediction of Mortality, Severity, and Length of Stay in the Intensive Care Unit of Sepsis Patients Based on Sepsis 3.0 by Machine Learning Models

Longxiang Su, Xu Zheng, Fengxiang Chang, Yingying Ma, Shengjun Liu, Huizhen Jiang, Hao Wang, Dongkai Li et al.

Frontiers in Medicine 2021 cited by 75

Medicine & Health Sepsis Diagnosis and Treatment ai assisted importance 7/10 scale stated

Clinicians find it difficult to predict early outcomes (mortality, severity, length of ICU stay) for sepsis patients in intensive care.

Details Source Open-access PDF model: logistic regression, random forest, XGBoos...

Machine learning to predict cardiovascular risk

José A. Quesada, Adriana López‐Pineda, Vicente Francisco Gil-Guillén, Ramón Durazo-Arvizú, Domingo Orozco‐Beltrán, Angela López-Domenech, Concepción Carratalá‐Munuera

International Journal of Clinical Practice 2019 cited by 104

Medicine & Health Artificial Intelligence in Healthcare ai assisted importance 7/10 scale stated

Accurately estimating a patient's cardiovascular event risk is difficult, and traditional scales may be outperformed by data-driven methods.

Details Source Open-access PDF model: 15 machine learning methods; best was quad...

Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data

Elham Yousef Kalafi, Nurul Aqilah Mohd Nor, Nur Aishah Mohd Taib, Mogana Darshini Ganggayah, Christopher P. Town, Sarinder Kaur Dhillon

Folia Biologica 2019 cited by 108

Medicine & Health Artificial Intelligence in Healthcare ai assisted importance 7/10 scale stated

Predicting breast cancer survival is needed to help select the best treatment protocols for patients.

Details Source Open-access PDF model: multilayer perceptron (MLP), random forest...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

David R. Kelley, Yakir Reshef, Maxwell L. Bileschi, David Belanger, Cory Y. McLean, Jasper Snoek

Genome Research 2018 cited by 534

Biology & Life Sciences Genomics and Chromatin Dynamics solved importance 7/10 scale stated

Predicting which DNA sequences act as regulatory elements and how genetic variants influence gene expression in specific cell types, from sequence alone.

Details Source Open-access PDF model: convolutional neural networks

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Yi Ding, Aarti Bagul et al.

arXiv (Cornell University) 2017 cited by 1,220

Medicine & Health COVID-19 diagnosis using AI partially solved importance 7/10 scale stated

Detecting pneumonia accurately from chest X-rays, a task normally requiring expert radiologist interpretation.

Details Source Open-access PDF model: CheXNet, a 121-layer convolutional neural...

Deep learning for electrocardiogram interpretation: Bench to bedside

Bas B.S. Schots, Camila S. Pizarro, Bauke K. O. Arends, Marish I.F.J. Oerlemans, Dino Ahmetagić, Pim van der Harst, René van Es

European Journal of Clinical Investigation 2025 cited by 26

Medicine & Health ECG Monitoring and Analysis partially solved importance 7/10 scale stated

Automating ECG analysis to detect and predict rhythm, conduction, ischemic and structural heart diseases, where clinical integration of algorithms remains limited.

Details Source Open-access PDF model: not stated in source

Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion

Prajwal Sanjay Pisal, Ondřej Krejčí, Patrick Rinke

npj Computational Materials 2025 cited by 25

Climate & Environment Machine Learning in Materials Science ai assisted importance 7/10 scale stated

Achieving high methanol yields and stable catalysts for CO2 thermoreduction remains a significant challenge for closing the carbon cycle.

Details Source Open-access PDF model: machine-learned force fields; unsupervised...

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Kwang S. Kim

Advanced Energy Materials 2025 cited by 43

Engineering & Materials Machine Learning in Materials Science ai assisted importance 7/10 scale stated

Discovering energy materials is slow because quantum-accurate simulations (DFT) are computationally expensive and chemical space is vast.

Details Source Open-access PDF model: graph neural networks, sparse Gaussian pro...

Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition

Tudor‐Stefan Cotet, Igor Krawczuk, Filippo Stocco, Noelia Ferruz, Anthony Gitter, Yoichi Kurumida, Lucas de Almeida Machado, Francesco Paesani et al.

bioRxiv (Cold Spring Harbor Laboratory) 2025 cited by 26

Biology & Life Sciences Protein Structure and Dynamics partially solved importance 7/10 scale stated

Designing proteins that bind EGFR, a key cancer drug target, is difficult and lacks standardized benchmarks.

Details Source Open-access PDF model: not stated in source

Morphological profiling for drug discovery in the era of deep learning

Qiaosi Tang, Ranjala Ratnayake, Gustavo de Miranda Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci et al.

Briefings in Bioinformatics 2024 cited by 46

Medicine & Health Cell Image Analysis Techniques ai assisted importance 7/10 scale stated

Analyzing large-scale high-content cell images to understand compound mechanism-of-action, drug repurposing, and morphodynamics under perturbation.

Details Source Open-access PDF model: not stated in source

A reproducible ensemble machine learning approach to forecast dengue outbreaks

Alessandro Sebastianelli, Dario Spiller, Raquel Carmo, James Wheeler, Artur Nowakowski, Ludmilla Viana Jacobson, Dohyung Kim, Hanoch Barlevi et al.

Scientific Reports 2024 cited by 66

Medicine & Health Mosquito-borne diseases and control ai assisted importance 7/10 scale stated

Dengue outbreaks are hard to predict countrywide because incidence varies across regions and time.

Details Source Open-access PDF model: not stated in source

Enhancing PET Degrading Enzymes: A Combinatory Approach

Yvonne Joho, Santana Royan, Alessandro T. Caputo, Sophia Newton, Thomas S. Peat, Janet M. Newman, Colin J. Jackson, Albert Ardèvol

ChemBioChem 2024 cited by 29

Climate & Environment Enzyme Catalysis and Immobilization ai assisted importance 7/10 scale stated

Plastic PET waste accumulates as a major environmental issue, and natural PET-degrading enzymes need improved efficiency for enzymatic recycling.

Details Source Open-access PDF model: machine learning (no specific model named)

Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme

Simon d’Oelsnitz, Daniel J. Diaz, Wantae Kim, Daniel J. Acosta, Tyler L. Dangerfield, Mason W. Schechter, Matthew B. Minus, James R. Howard et al.

Nature Communications 2024 cited by 56

Biology & Life Sciences Enzyme Catalysis and Immobilization partially solved importance 7/10 scale stated

Industrial biomanufacturing of therapeutic Amaryllidaceae alkaloids like the Alzheimer's drug galantamine is slow, and supply relies on extraction from low-yielding daffodils.

Details Source Open-access PDF model: MutComputeX (structure-based residual neur...

Machine Learning Predicts Cardiovascular Events in Patients With Diabetes: The Silesia Diabetes-Heart Project

Katarzyna Nabrdalik, Hanna Kwiendacz, Karolina Drożdż, Krzysztof Irlik, Mirela Hendel, Agata M. Wijata, Jakub Nalepa, Elon Correa et al.

Current Problems in Cardiology 2023 cited by 32

Medicine & Health Artificial Intelligence in Healthcare ai assisted importance 7/10 scale stated

Patients with diabetes are at high risk of cardiovascular events, and predicting which patients will suffer events is difficult.

Details Source Open-access PDF model: NCA with hybrid sampling/boosting; multipl...