Table 3.

Statistics of all the curated AI-solvable clinical trial datasets.

Tasks	# trials (I/II/III/IV)	# drugs	# med device	# other inter	# diseases	Intervention study (%)
trial duration forecasting	143.8K (13.5K/13.4K/9.2K/7.1K)	40.8K	21.1K	83.6K	44.6K	77.3%
patient dropout event forecasting	62.1K (4.2K/15.8K/11.5K/6.9K)	29.7K	10.9K	20.7K	21.9K	94.5%
serious adverse event forecasting	31.3K (2.0K/8.1K/4.8K/2.9K)	15.9K	6.6K	12.4K	15.9K	96.0%
mortality event prediction	31.3K (2.0K/8.1K/4.8K/2.9K)	15.9K	6.6K	12.4K	15.9K	96.0%
trial approval forecasting	43.2K (4.5K/12.5K/9.2K/4.5K)	24.1K	3.3K	12.6K	19.5K	93.0%
trial failure reason identification	41.4K (4.3K/8.8K/4.2K/3.5K)	17.7K	6.6K	16.9K	21.9K	86.8%
eligibility criteria design	136.4K (19.4K/14.2K/10.8K/10.6K)	48.5K	16.2K	75.0K	36.6K	84.9%
drug dose finding	12.8K (0/12.8K/0/0)	11.0K	0.1K	1.2K	7.3K	100%