How important was the problem?

Distribution

Where the source states the scale

Ranked by importance, with the scale the source itself gives.

• A Systematic Review of Machine Learning and IoT Applied to the Prediction and Monitoring of Cardiovascular Diseases

  10/10 · 17.9 million deaths per year worldwide

• Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model

  10/10 · 17 million+ global cases and 671,500 deaths as of July 30, 2020

• Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential

  10/10 · 186-patient cohort studied; pandemic scale itself not quantified

• Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning

  10/10 · not stated in source

• A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach

  10/10 · third leading cause of death in the world

• Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization

  10/10 · one of the top 10 leading causes of death

• Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction

  10/10 · leading global cause of death

• Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning

  9/10 · global pandemic; 0.9M sequences, most countries

• SIMLR: Machine Learning inside the SIR Model for COVID-19 Forecasting

  9/10 · COVID-19 epidemic across Canada and the United States

• Deep learning approaches for breast cancer detection in histopathology images: A review

  9/10 · one of the leading causes of death in women worldwide

• MGP-AttTCN: An interpretable machine learning model for the prediction of sepsis

  9/10 · 5.4 million deaths worldwide per year; more than 16 billion dollars in healthcare cost in the USA alone

• Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals

  9/10 · not stated in source

• Deep Learning Based Lung Cancer Detection and Classification

  9/10 · leading cause of mortality worldwide; survival rises 14% to 49% with timely diagnosis

• An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning

  9/10 · global pandemic; 375 patients in study

• Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins

  9/10 · not stated in source

• Detection and analysis of COVID-19 in medical images using deep learning techniques

  9/10 · not stated in source

• Deep Learning-Based Decision-Tree Classifier for COVID-19 Diagnosis From Chest X-ray Imaging

  9/10 · global pandemic

• A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)

  9/10 · global pandemic; prevalence rising every day throughout the globe (no numbers given)

• Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques

  9/10 · not stated in source

• De novo design of protein structure and function with RFdiffusion

  9/10 · not stated in source

Top 50 by rated importance

• Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction

  Cardiovascular disease, the leading global cause of death, needed better risk identification from accessible data.

  Medicine & Health · 2023 · ai assisted · 10/10 importance

• A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach

  Accurate early prediction of stroke is needed to enable timely treatment, but medical data is imbalanced.

  Medicine & Health · 2022 · partially solved · 10/10 importance

• Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning

  Cardiovascular disease often goes undiagnosed until serious events; non-invasive diagnosis from retinal images and DXA scans was lacking in Qatar.

  Medicine & Health · 2022 · partially solved · 10/10 importance

• Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization

  Detecting tuberculosis accurately and early from chest X-ray images, since late diagnosis can be life-threatening.

  Medicine & Health · 2020 · ai assisted · 10/10 importance

• A Systematic Review of Machine Learning and IoT Applied to the Prediction and Monitoring of Cardiovascular Diseases

  Cardiovascular disease is the leading cause of death worldwide (~17.9 million deaths/year), and early detection, prediction and monitoring are needed.

  Medicine & Health · 2023 · partially solved · 10/10 importance

• Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model

  Forecasting the 60-day trajectory of total COVID-19 infections in the USA, Brazil, India and Russia to support pandemic planning.

  Medicine & Health · 2020 · ai assisted · 10/10 importance

• Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential

  Predicting and managing COVID-19 disease severity was difficult, and mechanisms underlying severity were unclear.

  Medicine & Health · 2021 · partially solved · 10/10 importance

• Evolutionary-scale prediction of atomic-level protein structure with a language model

  Predicting the 3D structures of the exponentially growing catalog of protein sequences was too slow with existing methods, requiring a breakthrough in folding speed.

  Biology & Life Sciences · 2023 · solved · 9/10 importance

• AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

  Structural coverage of known protein-sequence space was limited; the paper delivers an openly accessible database of high-accuracy predicted protein structures.

  Biology & Life Sciences · 2021 · solved · 9/10 importance

• Accurate prediction of protein structures and interactions using a three-track neural network

  Predicting accurate 3D protein structures and protein-protein complexes from sequence information alone remained a major challenge.

  Biology & Life Sciences · 2021 · solved · 9/10 importance

• De novo design of protein structure and function with RFdiffusion

  Designing new proteins with specified structures and functions (binders, symmetric assemblies, enzyme scaffolds) lacked a general deep-learning framework.

  Biology & Life Sciences · 2023 · solved · 9/10 importance

• Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment

  Fast, reliable diagnosis of COVID-19 from chest CT scans and X-ray images was needed during the pandemic.

  Medicine & Health · 2021 · ai assisted · 9/10 importance

• Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques

  Predicting cardiovascular disease from clinical data to support earlier decisions and interventions.

  Medicine & Health · 2019 · ai assisted · 9/10 importance

• SIMLR: Machine Learning inside the SIR Model for COVID-19 Forecasting

  Forecasting the number of newly infected people one to four weeks ahead during the COVID-19 epidemic is hard because government policies change over time.

  Medicine & Health · 2022 · partially solved · 9/10 importance

• Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning

  Public health needs early prediction of new SARS-CoV-2 variant surges to prepare for immune escape and increased transmissibility.

  Medicine & Health · 2022 · partially solved · 9/10 importance

• MGP-AttTCN: An interpretable machine learning model for the prediction of sepsis

  Sepsis kills about 5.4 million people worldwide each year and costs over 16 billion dollars in the USA alone, and early detection in hospitals is difficult.

  Medicine & Health · 2021 · ai assisted · 9/10 importance

• Deep Learning Based Lung Cancer Detection and Classification

  Lung cancer must be detected early from CT scans, since late diagnosis sharply reduces survival rates.

  Medicine & Health · 2020 · partially solved · 9/10 importance

• An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning

  Healthcare systems under pandemic pressure needed fast, early assessment of COVID-19 patient severity to allocate resources and reduce mortality.

  Medicine & Health · 2021 · ai assisted · 9/10 importance

• Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins

  Predicting protein structures and designing functional proteins (efficient biocatalysts, bioactive proteins) is key to medicine, diagnostics and sustainable chemical manufacture. The paper reviews computational tools addressing this.

  Biology & Life Sciences · 2024 · ai assisted · 9/10 importance

• Detection and analysis of COVID-19 in medical images using deep learning techniques

  Rapid, automatic detection of COVID-19 from X-ray and CT medical images.

  Medicine & Health · 2021 · ai assisted · 9/10 importance

• Deep learning approaches for breast cancer detection in histopathology images: A review

  Detecting and classifying breast cancer from histopathology images automatically, since manual analysis is essential but challenging.

  Medicine & Health · 2024 · partially solved · 9/10 importance

• Deep Learning-Based Decision-Tree Classifier for COVID-19 Diagnosis From Chest X-ray Imaging

  COVID-19 testing demand overwhelmed capacity; RT-PCR is definitive but chest X-ray is fast and affordable, so AI detection of COVID-19 from CXR images was investigated.

  Medicine & Health · 2020 · partially solved · 9/10 importance

• A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)

  During the COVID-19 pandemic, clinicians needed rapid automatic diagnosis from medical imaging such as CT and X-ray.

  Medicine & Health · 2021 · ai assisted · 9/10 importance

• Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals

  Heartbeat events need accurate classification from single- or multi-lead ECG signals to support cardiovascular disease screening and diagnosis.

  Medicine & Health · 2020 · ai assisted · 9/10 importance

• Robust deep learning–based protein sequence design using ProteinMPNN

  Designing amino acid sequences that fold into target protein structures relied on physically based approaches such as Rosetta rather than deep learning.

  Biology & Life Sciences · 2022 · solved · 8/10 importance

• Accurate structure prediction of biomolecular interactions with AlphaFold 3

  Predicting the joint 3D structures of biomolecular complexes (proteins with ligands, nucleic acids, ions and antibodies) previously required separate specialized tools with limited accuracy. AlphaFold 3 addresses this unified modelling problem.

  Biology & Life Sciences · 2024 · solved · 8/10 importance

• Deep Residual Learning for Image Recognition

  Very deep neural networks were difficult to train, blocking accuracy gains from increased depth in visual recognition.

  Software & Coding · 2016 · solved · 8/10 importance

• ImageNet classification with deep convolutional neural networks

  Accurately classifying 1.2 million high-resolution images into 1000 categories, a task previous methods handled poorly.

  Software & Coding · 2017 · solved · 8/10 importance

• Faster sorting algorithms discovered using deep reinforcement learning

  Improving the efficiency of fundamental sorting routines had stalled for both human scientists and computational approaches.

  Software & Coding · 2023 · solved · 8/10 importance

• Learning skillful medium-range global weather forecasting

  Producing accurate 10-day global weather forecasts, traditionally requiring heavy compute rather than learning from historical weather data.

  Climate & Environment · 2023 · solved · 8/10 importance

• Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer

  Detecting methane point-source emissions from satellites was limited by trade-offs between coverage, resolution and detection accuracy.

  Climate & Environment · 2024 · solved · 8/10 importance

• CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV

  TB in HIV-positive patients often goes undiagnosed, and chest x-ray diagnosis is difficult due to atypical presentation and radiologist shortages.

  Medicine & Health · 2020 · ai assisted · 8/10 importance

• Protein structure prediction using deep learning distance and hydrogen‐bonding restraints in CASP14

  Predicting 3D protein structures from sequence, especially hard free-modelling (FM) targets without templates, in CASP14.

  Biology & Life Sciences · 2021 · partially solved · 8/10 importance

• Deep-learning-enabled antibiotic discovery through molecular de-extinction

  Antibiotic resistance requires new antimicrobial candidates; the work mines proteomes of extinct organisms for antibiotic peptides.

  Medicine & Health · 2024 · ai assisted · 8/10 importance

• A generalized platform for artificial intelligence-powered autonomous enzyme engineering

  Engineering proteins with desired functions is slow, expensive, and dependent on specialist expertise.

  Biology & Life Sciences · 2025 · solved · 8/10 importance

• Analysis of distance‐based protein structure prediction by deep learning in CASP13

  Predicting 3D protein structures from sequence alone, especially for free-modeling targets without templates, was a major unsolved challenge.

  Biology & Life Sciences · 2019 · partially solved · 8/10 importance

• Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare

  Sepsis is a leading cause of hospital death and hard to predict early because its signs resemble less critical conditions.

  Medicine & Health · 2021 · ai assisted · 8/10 importance

• Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13

  Predicting protein 3D structures from sequence, including template-free (ab initio) cases where no similar known structure exists.

  Biology & Life Sciences · 2019 · partially solved · 8/10 importance

• Pre-existing and machine learning-based models for cardiovascular risk prediction

  Cardiovascular risk prediction models needed assessment and improvement using large, complex healthcare data for primary prevention.

  Medicine & Health · 2021 · ai assisted · 8/10 importance

• Large-scale pancreatic cancer detection via non-contrast CT and deep learning

  Pancreatic ductal adenocarcinoma is typically detected late and inoperable, and identifying it on non-contrast CT was long considered impossible.

  Medicine & Health · 2023 · partially solved · 8/10 importance

• A foundation model for generalizable disease detection from retinal images

  AI models for retinal image analysis typically require large labeled datasets and are task-specific, limiting generalizable detection of eye and systemic diseases.

  Medicine & Health · 2023 · partially solved · 8/10 importance

• Predicting Rapid Intensification in North Atlantic and Eastern North Pacific Tropical Cyclones Using a Convolutional Neural Network

  Predicting rapid intensification of tropical cyclones in the North Atlantic and eastern North Pacific, where storms suddenly strengthen faster than traditional guidance anticipates.

  Climate & Environment · 2022 · partially solved · 8/10 importance

• A Deep Analysis of Transfer Learning Based Breast Cancer Detection Using Histopathology Images

  Breast cancer, common and dangerous in women and men, needs accurate detection from histopathology images containing phenotypic data.

  Medicine & Health · 2023 · ai assisted · 8/10 importance

• Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes**

  Antimicrobial resistance and a stalled antibiotic pipeline make new antimicrobial compounds urgently needed; metal complexes are promising but understudied.

  Medicine & Health · 2023 · solved · 8/10 importance

• Predicting High-Risk Prostate Cancer Using Machine Learning Methods

  PSA-based prostate cancer screening produces both false positives and false negatives, making it hard to identify which patients have high-risk prostate cancer.

  Medicine & Health · 2019 · partially solved · 8/10 importance

• Deep Learning-driven research for drug discovery: Tackling Malaria

  Discovering new antimalarial drug candidates is slow and expensive, and parasites constantly develop resistance to current drugs.

  Medicine & Health · 2020 · ai assisted · 8/10 importance

• A deep learning algorithm for detecting acute myocardial infarction

  Acute myocardial infarction is delayed or misdiagnosed in daily practice, and 12-lead ECG interpretation needs strengthening.

  Medicine & Health · 2021 · ai assisted · 8/10 importance

• Discovery of senolytics using machine learning

  Only a few senolytics (drugs eliminating senescent cells) are known, and experimental screening for new ones is costly.

  Medicine & Health · 2023 · partially solved · 8/10 importance

• Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14

  Predicting and refining protein 3D tertiary structures from sequence remains difficult and computationally expensive.

  Biology & Life Sciences · 2021 · partially solved · 8/10 importance

• Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy

  Rapid, reliable differentiation of COVID-19 from non-COVID-19 patients using bedside chest x-rays was needed during the Lombardy outbreak.

  Medicine & Health · 2021 · ai assisted · 8/10 importance