+ HEALTH Rationale and objectives To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (…± HEALTH Rationale and objectives The international application of artificial intelligence (AI) for lesion detection b…± HEALTH Rationale and objectives To address the challenge of preoperative prediction of synchronous liver metastasis…± HEALTH Objectives To conduct a nationwide survey among professionals working in oncology departments in China to inv…+ HEALTH The utilization of deep convolutional neural networks for the purpose of diagnosing diseases in the skin area…± HEALTH BACKGROUND . Gadolinium-based contrast agents remain essential for MRI but carry risks. Deep learning (DL) me…+ SCIENCE Gas Chromatography is a versatile separation technique widely used in analytical chemistry for constituent de…+ HEALTH Background Intracardiac echocardiography (ICE) facilitates left atrial (LA) reconstruction during atrial fibr…
TruaceTracing the truth around AIThursday, August 27, 2026
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The Index

What the evidence says.What the public feels.

Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.

1,168 results
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AI gains · 649

68
GainLabor· Stable· Evidence: Moderate (1 source)

AI adoption in organizations can improve work practices by increasing efficiency, productivity, and innovation.

A systematic literature review published November 28, 2024 examined how artificial intelligence is transforming organizational landscapes. It found AI reshapes work practices through automation and changes to decision making and employee roles, while driving cultural shifts toward innovation, agility, and continuous learning.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%92

Updated Jul 19, 2026 · TRV-2026-0273

68
GainScience· Stable· Evidence: Moderate (1 source)

Deep learning drives advancements in biology, chemistry, and physics by facilitating analysis of protein folding, molecular discovery, and particle interactions.

As of November 27, 2024, this peer-reviewed review paper surveys the state of deep learning, describing its role as a core component of modern AI and summarizing evolution from CNNs and RNNs to transformers, GANs, capsule networks, and GNNs, plus training methods like self-supervised, federated, and deep reinforcement learning.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%92

Updated Jul 19, 2026 · TRV-2026-0272

68
GainHealth· Stable· Evidence: Moderate (1 source)

Machine learning models that incorporate compressed respiratory and oxygenation timeseries improved early prediction of BPD at 7 days after birth compared to clinical-data-only models.

In a retrospective study of 513 preterm infants in a neonatal intensive care unit between 2009-2015, investigators developed machine learning models to predict bronchopulmonary dysplasia within one week after birth using clinical data and respiratory and oxygenation timeseries. The best model combined clinical data with advanced timeseries features processed by a long short-term memory network, achieving AUC 0.83.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%92

Updated Jul 19, 2026 · TRV-2026-0270

68
GainHealth· Stable· Evidence: Moderate (1 source)

Deep learning models, especially U-Net variants and newer transformer ensembles, improved ischemic stroke lesion segmentation on MRI, achieving Dice scores above 0.80 and approaching 0.90 in multisite DWI reports, to support faster treatment selection and quantification.

By July 2026, a narrative review of 40 studies from 2020-2025 found deep learning, led by U-Net variants with residual and attention mechanisms and standardized pipelines like nnU-Net, increasingly achieved high Dice scores on MRI DWI/ADC, with many reports above 0.80 and recent transformer and ensemble multisite models approaching 0.90, while CT performance was lower and more variable.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%92

Updated Jul 19, 2026 · TRV-2026-0268

AI problems · 519

56
ProblemMedia & Arts· Stable· Evidence: Moderate (1 source)

Suno's AI music generator was shown to have scraped decades of audio for training after a hacker accessed internal source code via employee credentials.

A hacker gained access to Suno's internal source code by using an employee's credentials, and the code review that followed exposed the company's audio collection practices for its AI music generator.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%92

Updated Jul 16, 2026 · TRV-2026-0231

56
ProblemMedia & Arts· Stable· Evidence: Moderate (1 source)

Suno's AI music models were powered by data pulled from third-party streaming services and lyric sites including YouTube Music, Deezer and Genius

By July 15, 2026, a new hack revealed the sourcing behind Suno's AI music service, showing the company pulled from streaming services and websites such as YouTube Music, Deezer and Genius to power its product and models.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%92

Updated Jul 16, 2026 · TRV-2026-0230

56
ProblemMedia & Arts· Stable· Evidence: Moderate (1 source)

The same caring Optimization System flattens culture, tamps down places and people, and carefully manages humanity's decline into obsolescence.

The Guardian review of D-topia on 2026-07-14 describes a far-future non-Earth planet run by an Optimization System that appears as cute droids and controls architecture and weather to maximize happiness. The player is a Facilitator performing low-friction grid maths puzzles and helping residents like Tot, who has a brain chip, and Eebie, who wants expressive fashion.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%92

Updated Jul 16, 2026 · TRV-2026-0229

56
ProblemPolicy· Stable· Evidence: Moderate (1 source)

AI used in the uncrewed systems can hallucinate and generate false results, creating risk of technical failure during autonomous operations.

In July 2026 the Royal Netherlands Navy began a five-week trial off Den Helder to test uncrewed surface vessels, aerial drones and underwater mine mappers operating as a coordinated system controlled by software, with the GeoSea vessel as a test base. The effort is part of a plan to have more than half of naval work done by uncrewed systems within five years and to eventually surround crewed ships with autonomous rings.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%92

Updated Jul 16, 2026 · TRV-2026-0228

Recomputed live from the record · Aug 27, 2026, 11:22 AM