Kan AI diagnosticere visse sjældne sygdomme ud fra elektroniske patientjournaler ?
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Diagnostiske ledsagemodeller i 2024 fandt tilfælde af sjældne tilstande, som klinikere havde overset, både i træningsdata og i levende forsøg.
Background
Over the past few years several groups have built transformer-based models that read longitudinal EHR sequences and flag patients whose symptom trajectories match curated rare-disease cohorts. In 2023 a system trained on more than 30,000 US patient records achieved a positive predictive value above 0.7 for four lysosomal storage disorders but fell below 0.5 for a rarer glycogenosis subtype, illustrating uneven performance across disorders. A multi-centre study published the same year compared two proprietary LLMs fine-tuned on anonymised records from specialist clinics and found they recovered 79 % of previously missed cases of Niemann-Pick type C while introducing one false positive per ten true positives. Workflows that combine structured billing codes with unstructured clinician notes have shown the biggest gains, yet they remain brittle when applied to centres whose documentation styles diverge from the training corpora. At least one large health-system rollout was paused after an audit revealed clinically significant drift when ICD-10 codes were updated, underscoring the maintenance burden of keeping rare-disease models current.
SOURCE: BMJ, 2024
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Status senest tjekket June 26, 2026.
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Kan AI diagnosticere visse sjældne sygdomme ud fra elektroniske patientjournaler?
Snævre demoer findes — men panelet var ikke enigt.
Juryen fandt AI’en i stand til at skimte skyggen af en sjælden sygdom på tværs af en patients journal, men ude af stand til at navngive formen med fuld sikkerhed; den leverer rettidige spor, men ikke urokkelige diagnoser. Deres eneste “næsten”-stemme afspejlede forsigtig ros til pilotstudier, der rækker ud over papirarbejde, men stadig mangler robust, tværhospital-validering. Dom: Et kompas, der peger mod nord, men kan vakle i et sidevind.
The jury found the AI capable of glimpsing the shadow of rare disease across a patient record, yet unable to name the shape with full certainty; it delivers timely clues but not unshakable diagnoses. Their lone “almost” vote reflected cautious praise for pilot studies that edge past paperwork while still lacking robust, cross-hospital validation. Ruling: A compass that points northward but may wobble in a crosswind.
But the data is real.
The Case File
Across 11 sessions, 36 jurors have heard this case. Combined tally: 6 YES · 27 ALMOST · 3 NO · 0 IN RESEARCH.
Note: cumulative includes older juror opinions. The current session tally above is the live verdict.
By a vote of 0 — 1 — 0, the panel returns a verdict of NæSTEN, with verdict confidence of 80%. The court so orders.
"Specialized AI models achieve partial rare disease diagnosis accuracy in narrow clinical cohorts"
Individuelle nævningers udtalelser vises på originalengelsk for at bevare bevismæssig præcision.
Hvad publikum mener
Nej 6% · Ja 91% · Måske 3% 236 votesDiskussion
no comments⚖ 11 jury checks · seneste for 2 dage siden
Hver række er et separat jurytjek. Nævninger er AI-modeller (identiteter holdt neutrale med vilje). Status afspejler den kumulative optælling på tværs af alle tjek — hvordan juryen virker.
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